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14,185 results for “phylogenies”
Fig. 1. Strict consensus tree resulting from equal weighting analysis. Jackknife values over 51 in Pseudocetherinae (Hemiptera: Reduviidae) revisited: phylogeny and taxonomy of the lobe-headed bugs
Fig. 1. Strict consensus tree resulting from equal weighting analysis. Jackknife values over 51 are reported for tree one of eight.
Supplementary material for: Phylogeny and biogeography of the ancient spider family Filistatidae (Araneae) is consistent both with long-distance dispersal and vicariance following continental drift
<p>Raw data and input files for phylogenetic and biogeographic analysis of the article "<strong>Phylogeny and biogeography of the ancient spider family Filistatidae (Araneae) is consistent both with long-distance dispersal and vicariance following continental drift</strong>".</p> <p><strong>Supplementary material S1. </strong>Matrix of phenotypic characters in .ss format.</p> <p><strong>Supplementary material S2. </strong>Alignment of COI sequences in fasta format..</p> <p><strong>Supplementary material S3. </strong>Alignment of H3 sequences in fasta format.</p> <p><strong>Supplementary material S4. </strong>Alignment of 16S sequences in fasta format before trimming with gblocks.</p> <p><strong>Supplementary material S5. </strong>Alignment of 28S sequences in fasta format before trimming with gblocks.</p> <p><strong>Supplementary material S6. </strong>Input for running parsimony analysis using TNT (phenotypic data only).</p> <p><strong>Supplementary material S7. </strong>Input for running Bayesian inference using MrBayes (phenotypic data only).</p> <p><strong>Supplementary material S8. </strong>Input for running parsimony analysis using TNT (sequence data only).</p> <p><strong>Supplementary material S9. </strong>Input for running Bayesian inference using MrBayes (sequence data only).</p> <p><strong>Supplementary material S10. </strong>Input for running parsimony analysis using TNT (total evidence).</p> <p><strong>Supplementary material S11. </strong>Input for running Bayesian inference using MrBayes (total evidence).</p> <p><strong>Supplementary material S12. </strong>Input for running parsimony analysis using TNT (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S13. </strong>Input for running Bayesian inference using MrBayes (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S14. </strong>Input for running Bayesian inference using MrBayes (total evidence) and estimating node ages using tip-dating.</p> <p><strong>Supplementary material S15. </strong>Input for running Bayesian inference using Beast (sequence data only) and estimating node ages using node-dating.</p> <p><strong>Supplementary material S16. </strong>Raw geographic distances among areas in each time slice and dispersal probability matrices for each biogeographic model.</p> <p><strong>Supplementary material S17. </strong>Inputs for estimating ancestral ranges and performing biogeographic stochastic maps for our dataset.</p> <p><strong>Supplementary material S18. </strong>Consensus tree found with parsimony analysis using TNT (phenotypic data only).</p> <p><strong>Supplementary material S19. </strong>Consensus tree found with Bayesian inference using MrBayes (phenotypic data only).</p> <p><strong>Supplementary material S20. </strong>Consensus tree found with parsimony analysis using TNT (sequence data only).</p> <p><strong>Supplementary material S21. </strong>Consensus tree found with Bayesian inference using MrBayes (sequence data only).</p> <p><strong>Supplementary material S22. </strong>Consensus tree found with parsimony analysis using TNT (total evidence).</p> <p><strong>Supplementary material S23. </strong>Consensus tree found with Bayesian inference using MrBayes (total evidence).</p> <p><strong>Supplementary material S24. </strong>Consensus tree found with parsimony analysis using TNT (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S25. </strong>Consensus tree found with Bayesian inference using MrBayes (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S26. </strong>Consensus tree found with Bayesian inference using MrBayes (total evidence) and with node ages estimated using tip-dating.</p> <p><strong>Supplementary material S27. </strong>Maximum clade credibility tree found with Bayesian inference using Beast (sequence data only) and with node ages estimated using node-dating.</p>
FIG. 3. — A in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 3. — A, BI phylogenetic tree estimated by mitochondrial 16S rRNA and; B, partial COI sequences depicting the phylogenetic relationships of Dendrelaphis Boulenger, 1890 species with BPP/UFB support at the branch nodes. Sequences generated in this study are shown in bold.
FIG. 2. — A in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 2. — A, Dendrelaphis biloreatus Wall, 1908 in life, showing anterior body and head from Kolasib, Mizoram, NE India. Inset: Dorso-lateral view of the head showing two loreal scales; B, juvenile Dendrelaphis biloreatus (MZMU1812) in life from MZU Campus, Mizoram, NE India, photographed by Tbc. Lalhruaitluangi. Inset: Antero-lateral view of the head showing single loreal scale, photographed by Romalsawma.
FIG. 6 in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 6. — Two specimens of Dendrelaphis proarchos Wall, 1909 found sheltered inside a green bamboo: A, from Kepran,photographed by Tbc. Mapuia; B, from Tlangnuam, photographed by C. Mawitea.
FIG. 7. — A in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 7. — A, Dendrelaphis cyanochloris (Wall, 1921) preying on adult Calotes emma Gray, 1845, photographed by R. Lalnunmawia; B, Dendrelaphis proarchos Wall, 1909 preying on adult Duttaphrynus melanostictus (Schneider,1799), photographed by Hawla Hmar Zote.
FIG. 5 in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 5. — Elevation map showing the specimens location of Dendrelaphis proarchos Wall, 1909 (green shapes), Dendrelaphis biloreatus Wall, 1908 (yellow shapes), Dendrelaphis cyanochloris (Wall, 1921) (red shapes), Dendrelaphis cf. vogeli LSUHC 6768 (purple circle with dot), and Dendelaphis cf. ngansonensis CAS221428 (blue circle with dot) examined in this study. Confirmed populations of Dendrelaphis proarchos (green circles) and Dendrelaphis biloreatus (yellow triangles) are based on Vogel & van Rooijen (2011a, b).
FIG. 4 in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 4. — BI phylogenetic tree estimated by mitochondrial Cytb sequences depicting phylogenetic relationships of Dendrelaphis Boulenger, 1890 species with BPP/UFB support at the branch nodes. Sequences generated in this study are shown in bold.
FIG. 1. — A in Contributions to the taxonomic status and molecular phylogeny of Asian Bronzeback Snakes (Colubridae, Ahaetuliinae, Dendrelaphis Boulenger, 1890), from Mizoram State, Northeast India
FIG. 1. — A, sub-adult Dendrelaphis proarchos Wall, 1909 from Mizoram, NE India; B, everted hemipenial sulcal side (right) and asulcal side (left) of Dendrelaphis proarchos from Mizoram, NE India; C, Adult Dendrelaphis cyanochloris (Wall, 1921) from Mizoram, NE India. Scale bar: B, 5 mm.
Fig. 3 in Application Of Dna Barcoding In Taxonomy And Phylogeny: An Individual Case Of Coi Partial Gene Sequencing From Seven Animal Species
Fig. 3. Phylogenetic position of Macrobiotus sp., Bayesian inference phylogenetic tree. Sequences obtained by us are written in bold.
Fig. 1 in Application Of Dna Barcoding In Taxonomy And Phylogeny: An Individual Case Of Coi Partial Gene Sequencing From Seven Animal Species
Fig. 1. Phylogenetic position of D. lindholmi and L. a. exigua, Bayesian inference phylogenetic tree. Sequences obtained by us are written in bold.
Data from: Leme et al. (2022) New genera and a new species in the "Cryptanthoid Complex" (Bromeliaceae: Bromelioideae) based on the morphology of recently discovered species, seed anatomy, and improvements in molecular phylogeny. Phytotaxa (doi: 10.11646/phytotaxa.544.2.2)
<p>DNA sequence alignments as well as the input and output files which specify the different data partitioning schemes used for phylogenetic analyses in Leme et al. (2022) New genera and a new species in the “Cryptanthoid Complex” (Bromeliaceae: Bromelioideae) based on the morphology of recently discovered species, seed anatomy, and improvements in molecular phylogeny. Phytotaxa. (doi: 10.11646/phytotaxa.544.2.2)</p>
Data from: Composition of a chemical signalling trait varies with phylogeny and precipitation across an Australian lizard radiation
<p>The environment presents challenges to the transmission and detection of animal signalling systems, resulting in selective pressures that can drive signal divergence among populations in disparate environments. For chemical signals, climate is a potentially important selective force because factors such as temperature and moisture influence the persistence and detection of chemicals. We investigated an Australian lizard radiation (<em>Heteronotia</em>) to explore relationships between a sexually dimorphic chemical signalling trait (epidermal pore secretions) and two key climate variables: temperature and precipitation. We reconstructed the phylogeny of <em>Heteronotia</em> with exon capture phylogenomics, estimated phylogenetic signal in among-lineage chemical variation, and assessed how chemical composition relates to temperature and precipitation using multivariate phylogenetic regressions. High estimates of phylogenetic signal indicate that the composition of epidermal pore secretions varies among lineages in a manner consistent with Brownian motion; although there are deviations to this, with stark divergences coinciding with two phylogenetic splits. Accounting for phylogenetic non-independence, we found that among-lineage chemical variation is associated with geographic variation in precipitation but not temperature. This contrasts somewhat with previous lizard studies, which have generally found an association between temperature and chemical composition. Our results suggest that geographic variation in precipitation can affect the evolution of chemical signalling traits, possibly influencing patterns of divergence among lineages and species.</p> <p> </p>
EcoPhyloMapper: an R package for integrating geographic ranges, phylogeny, and morphology
<p>1. Spatial patterns of species richness, phylogenetic and morphological diversity are key to answering many questions in ecology and evolution. Across spatial scales, geographic and environmental features, as well as evolutionary history and phenotypic traits, are thought to play roles in shaping both local species communities and regional assemblages. By examining these geographic patterns, it is possible to infer how different axes of biodiversity influence one another, and how their interaction with abiotic factors has led to the spatial distribution of species assemblages – and their attributes – that we observe in the present. Although there has been interest in this area of research for some time, it has recently become more tractable to include multivariate shape data in such analyses. Shape information has the potential to provide a more direct measure of the functional morphology of species as compared to individual trait measurements and might be more relevant to understanding community composition. However, few tools currently exist to explore geographic patterns of both phylogenetic and shape diversity.</p> <p>2. We present the ecoPhyloMapper R package (epm) that aims to streamline the handling of geographic range polygons or point occurrences and integration of resulting species metacommunities with phylogenetic trees and morphological shape.</p> <p>3. Geographic maps can be generated that demonstrate spatial patterns in diversity metrics pertaining to phylogenetic similarity, multivariate shape similarity and disparity, and combinations of the two. Patterns of taxonomic, phylogenetic and shape disparity turnover can also be visualized. Biodiversity indices summarized across grid cells can easily be exported to GIS software as well as to other R packages that specialize in community assembly or geospatial statistics.</p> <p>4. This R package will facilitate the geographic exploration of multivariate shape data in concert with phylogenetic diversity, which will in turn support macroecological research exploring how species assemblages are structured. Further, this R package should prove useful across a wide range of macroecological applications that extend beyond the study of morphology.</p>
Fig. 3 in Phylogeny and classification of Odonata using targeted genomics
Fig. 3. Current state of odonate phylogeny. Summary of the phylogenetic hypothesis for Odonata from Fig. 2. Support values for each node can be found in Fig. 2. Grey text highlights both the reinstated (Tatocnemididae stat. res., Rhipidolestidae stat. res.) and the proposed new families (Protolestidae fam. nov., Priscagrionidae fam. nov., Mesopodagrionidae fam. nov., Mesagrionidae fam. nov., and Amanipodagrionidae fam. nov.). Discussion of Grps. 1, 2, 3, and 4 is found in the Calopterygoidea section of the manuscript. Almost all major lineages are included and now have a hypothesized phylogenetic placement. The zygopteran genera Rimanella (Rimanellidae) and Sciotropis (Incertae Sedis group 8) were not included in this analysis.
Fig. 2 in Phylogeny and classification of Odonata using targeted genomics
Fig. 2. AHE topology. Results of the phylogenetic reconstruction of Odonata using loci captured from anchored hybridization enrichment. A) ML and Bayesian phylogenetic reconstruction of the Odonata using 478 loci. AZ in the right hand column represents the suborder Anisozygoptera. See "key to nodal support" for a visual guide to nodal support. Support values of 100 bootstrap and 1.0 posterior probability are not shown. Quartet sampling (QS) that shows full support (1/NA/1) is not shown at the node but all other QS is shown at each node along with a measure of taxon rogueness (QF score) at each branch tip. Bolded GF scores represent the lowest values across the topology. Newly established or reestablished families are shown in grey text. B) Arepresentation of the branch lengths are shown with all three suborders designated.
Fig. 4 in Molecular phylogenies map to biogeography better than morphological ones
Fig. 4 The number of morphological and molecular trees most congruent with biogeography. Comparison of the number of trees in each sample (morphological or molecular) with a greater biogeographic fit than its counterpart. a Consistency index (CI), grey bars show totals for the whole sample, coloured bars indicate totals in the subset significantly different from the expected null (CI & RI p value <0.05). b Retention index (RI), grey bars show totals for the whole sample, coloured bars indicate totals in the subset significantly different from the expected null (CI & RI p value <0.05). c P values for the CI & RI random permutations (CI & RI p value), where grey bars show totals for the whole sample, coloured bars are clades with values <0.05. d biogeographic HER (bHER), counts are for the whole dataset. Bars show the number of clades in each subset, with binomial confidence intervals calculated using the approach of Clopper and Pearson103. N = 48 biologically independent pairs of morphological and molecular phylogenies.
Fig. 1 in Molecular phylogenies map to biogeography better than morphological ones
Fig. 1 Testing the biogeographic congruence of phylogenetic trees. a Defining biogeographic regions and coding taxon presences and absences. 1. Occurrence data on the distribution of extant species is used to produce a list of biogeographic regions for the clade and to summarise ranges for the taxa in the published phylogenies. 2. This distributional information is converted into a matrix of binary characters representing taxa in biogeographic regions, where 0 indicates the taxon is absent and 1 indicates the taxon is present. 3. Characters in the occurrence matrix are mapped onto the morphological and molecular phylogeny selected for each clade, allowing standard measures of character fit (CI, RI) to be calculated for each tree. b Presence and absence codings in each matrix are randomly reassigned to taxa, keeping the presence and absence codings fixed for each row. Characters form the new randomly permuted matrix are mapped onto the original trees and both CI and RI are recalculated. The entire randomisation process is performed 10,000 times. c The 10,000 CI and RI values from matrices' biogeographic region reassignments form a null distribution of expected congruence values if taxa in the clade were randomly distributed in biogeographic regions. The observed CI and RI of region characters for a given tree is compared to the null distribution for that same tree to determine whether the observed biogeographic congruence value lies outside of the 95% confidence interval.
Fig. 2 in Molecular phylogenies map to biogeography better than morphological ones
Fig. 2 Biogeographic congruence in morphological and molecular phylogenies. Binary biogeographic region characters mapped onto paired morphological and molecular phylogenies. a Placental mammals (Eutheria) from O'Leary et al. 2013100. b Caribbean boas (Chilabothrus/Epicrates), with the morphological tree taken from Kluge 1989101 and the molecular tree taken from Tolson 1987102. Regions for which the terminal taxon is coded present are represented as coloured pie slices. Consistency index (CI), retention index (RI) and biogeographic HER (bHER) values given are for the matrix of biogeographic region presences and absences, while CI & RI p value is calculated using 10,000 randomly permuted region matrices.
URL list for downloading training data for 'Maximum Likelihood Phylogeny Reconstruction'' (Galaxy Training Material)
<p>This data is used for Galaxy Training Network (GTN) training 'Maximum Likelihood Phylogeny Reconstruction'. It is a list of Zenodo URL pointers to a dataset of 173 amino acid alignments of orthologs found in chromosome 5 of four strains of S. cerevisiae. Original sequence data (https://zenodo.org/record/6610704) was processed in Galaxy following GTN 'Preparing genomic data for phylogeny reconstruction' training (10.48546/workflowhub.workflow.359.1) to generate alignments of orthologs.</p>
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