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501 results for “Phylogenetic tree”
Datasets for phylogenetic analyses and phylogenetic trees for: Genetic barcodes for species identification and phylogenetic estimation in ghost spiders (Araneae: Anyphaenidae: Amaurobioidinae). Invertebrate Systematics, 2024
<p>We combined the COI sequence data with legacy multigene sequence data to create a new, taxon-rich phylogeny for the Amaurobioidinae. We used sequences for four loci that have been used in previous studies on the subfamily: two mitochondrial loci, COI (658bp) and ribosomal subunit 16S (16S, 410bp); and two nuclear loci, Histone H3 (H3, 327bp) and ribosomal subunit 28S (28S, 839bp). We complemented the Amaurobioidinae data with sequences from several non-amaurobioidine anyphaenids and two clubionids as outgroups. Sequence alignment was performed using the MAFFT (ver. 7.308) plugin in Geneious, allowing MAFFT to automatically select an appropriate alignment strategy based on the properties of each locus, or with the online MAFFT server (https://mafft.cbrc.jp), which consistently selected the L-INS-i algorithm. Finally, alignments of the four loci were concatenated to construct a 2234 bp multigene sequence matrix containing 692 taxa, with about 55% missing/gap data (“full” matrix henceforth). To ensure that excessive missing data did not affect the resulting topology, we also constructed a reduced matrix by removing additional COI-only specimens so that each species and morphotype was represented by just one or two specimens for which all loci were available (where possible). After realignment, this reduced matrix was 2235 bp long, included 167 taxa, and had about 22% missing/gap data (“reduced” matrix henceforth). Phylogenetic analyses under maximum likelihood, including model selection, were then conducted with IQ-TREE 2. We performed phylogenetic analyses on both concatenated matrices (the full matrix and the reduced matrix) and on each individual locus. For model selection, we provided an initial scheme that partitioned the matrix by locus, and further partitioned the protein-coding loci (COI and H3) by codon position. We used ModelFinder and searched for the best partition scheme, all in IQ-TREE. The best models (partitions) for the full dataset were: GTR+F+I+G4 (16S), GTR+F+I+I+R4 (28S), TVM+F+I+I+R2 (COI-1), TIM2+F+R4 (COI-2), GTR+F+R5 (COI-3), TVMe+G4 (H3-1-H3-2), SYM+G4 (H3-3); and for the reduced dataset: GTR+F+I+G4 (16S), GTR+F+I+G4: (28S), GTR+F+I+G4: (COI-2), GTR+F+I+G4: (COI-3), TVM+F+I+G4: (COI-1, H3-2), GTR+F+I+G4: (H3-1), GTR+F+I+G4: (H3-3). For each dataset, once the best models and partitions were defined, we executed 10 independent replicates of tree calculations followed by 1000 ultrafast bootstrap replicates, and the replicate reaching the maximum likelihood was chosen. Phylogenetic analyses under parsimony were made with TNT, under equal weights, using the “new technology” search with default values, asking for 10 independent hits to the minimal length, and submitting the resulting trees to a round of TBR branch swapping. </p>
How is tree growth rate linked to root functional traits in phylogenetically related poplar hybrids?
<p>Fine roots play a crucial role in soil nutrient and water acquisition, significantly contributing to tree growth. Fine roots with a high specific root length (SRL) and small diameter are often considered to help trees grow fast. However, inconsistencies in the literature do not provide a clear basis on the effect of root functional traits, such as SRL or root mass density (RMD), on tree growth rate in phylogenetically related trees. Our aim was to examine relationships between tree growth rate and root functional traits, using clones displaying different growth rates in a hybrid poplar plantation located in New Liskeard, ON, Canada. Fine roots (diameter < 2 mm) samples were collected using soil cores at depths of 0–20, 20–40 and 40–60 cm, and analyzed for morphological, chemical and architectural traits. High SRL and thin fine roots were associated with the least productive clones, which is not consistent with the root economics spectrum (RES) theory. However, the most productive clone had larger fine root diameter and higher root lignin concentrations, probably reducing root construction and maintenance costs and C losses. Therefore, at the 0–20 and 20–40 cm depths, tree growth rates showed positive correlations with root diameter and root lignin concentrations, but negative correlations with SRL and root soluble compounds concentration. Increasing RMD at the 0–20 cm depth promoted tree growth rates, showing the importance of soil exploration in the topsoil for tree growth. We conclude that fine root variation does not always follow the RES hypothesis and argue that the rapid growth rate of trees may also be driven by fine root growth in diameter and mass in phylogenetically related trees.</p>
Phylogenetic tree of the Kho-Bwa languages
<p>This is a phylogenetic tree of the Kho-Bwa languages spoken in Western Arunachal Pradesh, India. The map has been prepared using the data and methodology described in Wu, Bodt and Tresoldi (accepted). The map has also been used in Bodt (accepted).</p> <p>Wu, Mei-Shin, Timotheus A. Bodt & Tiago Tresoldi. accepted. Bayesian phylogenetics illuminate shallower relationships among Trans-Himalayan languages in the Tibet-Arunachal area. <em>Linguistics of the Tibeto-Burman Area.</em></p> <p>Bodt, Timotheus Adrianus. accepted. <em>Proto-Western Kho-Bwa: Reconstructing the past of a small indigenous community.</em> Academia Sinica Language and Linguistics monograph series.</p> <p> </p>
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 in Phylogenetic analysis and systematic position of two new species of the ant genus Crematogaster (Hymenoptera, Formicidae) from Southeast Asia
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 taxa using five genes (ArgK, CAD, LWRh, Top1, Wg) in a MrBayes analysis. Above node numbers indicate posterior probability. Data were partitioned by PartitionFinder v.1.1.1 and analyzed using a best fit model for each gene and codon position, with 10 million generations and a burn-in of 25 %. Area enclosed by dashed lines is enlarged on Fig. 2.
Fig. 2. Phylogenetic tree constructed with 57 in A review of Bennelongia De Deckker & McKenzie, 1981 (Crustacea, Ostracoda) species from eastern Australia with the description of three new species
Fig. 2. Phylogenetic tree constructed with 57 novel COI sequences of Bennelongia, 26 published Bennelongia sequences and one Heterocypris spec. as outgroup (sequence names are given in brackets at the end of species names). This tree represents two trees of identical topology inferred by ML and BI. Bootstrap values (for 1000 bootstrap replicates) from ML analyses and Bayesian posterior probabilities (ranging from 0 to 1) are shown for each node (in the format: 'Bootstrap Support/Posterior Probability'). Branch lengths are proportional to the genetic distance scale at the bottom left. Clades with published sequences have been collapsed; the number of sequences in these clades is included in brackets after the species name. Nodes with less than 50% bootstrap support and a posterior probability of less than 0.5 have been collapsed. The tree shows six strongly supported clades that correspond to the species presented in this study.
Neighbor-joining phylogenetic tree based on 16S rRNA sequences.
<p><strong>Supplementary Figure (S1):</strong> Bayesian 50% majority rule phylogram of 16S ribosomal RNA region showing the phylogenetic relationships among the bacterial isolates in our study. The newly generated sequences are preceded by red circle. The GenBank sequences are preceded by blue squares. The GenBank accession number appears after the species name. Numbers above the branches represent Bayesian posterior probabilities (≥ 0.90), and the maximum parsimony bootstrap support values are given below the branches (≥70%). The out group used for tree construction preceded by empty circle.</p>
Figure 1. Bayesian phylogenetic tree inferred from the 640 in Two new Geoplaninae species (Platyhelminthes: Continenticola) from Southern Brazil based on an integrative taxonomic approach
Figure 1. Bayesian phylogenetic tree inferred from the 640-bp of cytochrome c oxidase subunit I gene under GTR + I + G model of sequence evolution. The two new species are highlighted in light grey (Cratera ochra sp. nov.) and dark grey (Obama maculipunctata sp. nov.). Values indicate support for each node according to the maximum posterior probabilities>70% and bootstrap support values> 70%, respectively.
Data from: Enriching the ant tree of life: enhanced UCE bait set for genome-scale phylogenetics of ants and other Hymenoptera
1. Targeted enrichment of conserved genomic regions (e.g., ultraconserved elements or UCEs) has emerged as a promising tool for inferring evolutionary history in many organismal groups. Because the UCE approach is still relatively new, much remains to be learned about how best to identify UCE loci and design baits to enrich them. 2. We test an updated UCE identification and bait design workflow for the insect order Hymenoptera, with a particular focus on ants. The new strategy augments a previous bait design for Hymenoptera by (a) changing the parameters by which conserved genomic regions are identified and retained, and (b) increasing the number of genomes used for locus identification and bait design. We perform in vitro validation of the approach in ants by synthesizing an ant-specific bait set that targets UCE loci and a set of "legacy" phylogenetic markers. Using this bait set, we generate new data for 84 taxa (16/17 ant subfamilies) and extract loci from an additional 17 genome-enabled taxa. We then use these data to examine UCE capture success and phylogenetic performance across ants. We also test the workability of extracting legacy markers from enriched samples and combining the data with published data sets. 3. The updated bait design (hym-v2) contained a total of 2,590-targeted UCE loci for Hymenoptera, significantly increasing the number of loci relative to the original bait set (hym-v1; 1,510 loci). Across 38 genome-enabled Hymenoptera and 84 enriched samples, experiments demonstrated a high and unbiased capture success rate, with the mean locus enrichment rate being 2,214 loci per sample. Phylogenomic analyses of ants produced a robust tree that included strong support for previously uncertain relationships. Complementing the UCE results, we successfully enriched legacy markers, combined the data with published Sanger data sets, and generated a comprehensive ant phylogeny containing 1,060 terminals. 4. Overall, the new UCE bait design strategy resulted in an enhanced bait set for genome-scale phylogenetics in ants and likely all of Hymenoptera. Our in vitro tests demonstrate the utility of the updated design workflow, providing evidence that this approach could be applied to any organismal group with available genomic information.
Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details).
Supplementary Data for: A time-calibrated 'Tree of Life' of aquatic insects for knitting historical patterns of evolution and measuring extant phylogenetic biodiversity across the world
<p>This compendium of files includes the dated phylogenetic tree in Newick format (<strong>Data S1</strong>), the list of statistical routines used for the three empirical case studies (<strong>Data S2</strong>), and the high-resolution version of the figures in the supplementary materials and main text (<strong>Data S3</strong>) for the <em>Earth-Science Reviews</em> paper "A time-calibrated ‘Tree of Life’ of aquatic insects for knitting historical patterns of evolution and measuring extant phylogenetic biodiversity across the world", which is under consideration. The best-scoring molecular tree (<strong>Data S1</strong>) can be opened using freely available programs like R (R Development Core Team, 2021), Dendroscope (Huson and Scornavacca, 2012), and FigTree (Rambaut, 2018).</p> <p>Please, feel free to send an email to the maintainer Dr. Jorge García Girón (jogarg@unileon.es OR Jorge.Garcia-Giron@oulu.fi) if you face any trouble downloading, opening, or using these files.</p> <ul> <li>Huson, D. H., & Scornavacca, C. (2012). Dendroscope 3: An interactive tool for rooted phylogenetic trees and networks. <em>Systematic Biology</em>, <em>61(6)</em>, 1061–1067.</li> <li>R Development Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/</li> <li>Rambaut, A. (2018). FigTree. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK. http://tree.bio.ed.ac.uk/software/figtree/</li> </ul>
FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank in Superficially described and ignored for 92 years, rediscovered and emended: Apodera angatakere (Amoebozoa: Arcellinida: Hyalospheniformes) is a new flagship testate amoeba taxon from Aotearoa (New Zealand)
FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank
Fig. 6. Bayesian inference tree for 5519 in First Record of Poecilobdella nanjingensis (Hirudinida: Arhynchobdellida: Hirudinidae) from Taiwan and its Molecular Phylogenetic Position within the Family
Fig. 6. Bayesian inference tree for 5519 bp alignment positions of nuclear 18S rRNA, 28S rRNA, mitochondrial cytochrome c oxidase subunit I, and 12S rRNA markers. Numbers on nodes indicate bootstrap values for maximum likelihood and Bayesian inference posterior probabilities.
Fig. 3. Phylogenetic trees obtained from a concatenated dataset with a in Molecular Systematics and Morphological Analyses of the Subgenus Setihenricia (Echinodermata: Asteroidea: Henricia) from Japan
Fig. 3. Phylogenetic trees obtained from a concatenated dataset with a total length of 1,277 bp, consisting of seven mitochondrial genes (16S, tRNA-Ala, tRNA-Leu, tRNA-Asn, tRNA-Gln, tRNA-Pro, and COI). The trees were built based on maximum likelihood (ML, left) and Bayesian inference (BI, right). Values at nodes indicate bootstrap scores from ML and posterior probabilities from BI. Outgroups are only shown in the ML tree with both the support values. Scale bars indicate the number of nucleotide substitutions per site. OTUs sequenced in this study are in bold face. Each letter in parentheses after non-bold OTUs denotes the source: C, Chichvarkhin (2017b); F, Foltz and Rocha- Olivares (unpublished); K, Knott et al. (2018); L, Lopes et al. (2016); M, Matsubara et al. (2004); W, Wada et al. (1996). Circles indicate species listed as Setihenricia in Chichvarkhin and Chichvarkhina (2017). Triangles indicate species morphologically identified as Setihenricia in this study (see Fig. 4A).
Data from: Functional and phylogenetic dimensions of tree biodiversity reveal unique geographic patterns
<p>Aim: Quantify tree functional and phylogenetic richness and divergence at the global scale, and explore the drivers underpinning these biogeographic patterns.</p> <p>Location: Global</p> <p>Time Period: Present</p> <p>Major taxa studied: Trees </p> <p>Methods: Using global tree occurrence data, we outlined species' observed ranges using individual alpha hulls to obtain per-pixel tree species composition. Using eight traits from a recent tree-trait database and a vascular-plant phylogeny we computed and mapped four pixel level biodiversity indices, including two metrics related to richness: phylogenetic richness and functional richness and two related to divergence: mean pairwise phylogenetic distance and Rao's quadratic entropy. To account for the effect of species richness, we also calculated standardized effect sizes accounting for richness for each pixel. We then explored the relations between richness and divergence and the latitudinal patterns of divergence both globally and across biomes. Finally, we used a random forest modeling approach to test for drivers of the different dimensions of diversity in trees.</p> <p>Results: In contrast to the latitudinal gradient in species richness, functional and phylogenetic divergence both peak in mid-latitude systems, exhibiting the highest values in temperate ecosystems and lowest values in boreal and tropical forests. This result holds for functional divergence when removing gymnosperms but the peak flattens for phylogenetic divergence. Phylogenetic richness is consistently lower than expected given the number of species, whereas functional richness has higher-than-expected values at mid-latitudes, mimicking functional divergence patterns. When considering the drivers of these diversity patterns, temperature and historical speciation rates consistently emerge as the strongest forces driving divergence, with negligible effects of human influence, soils or historical climate stability.</p> <p>Main Conclusions: Collectively, these results reveal unique similarities and disparities across biomes that are not apparent in any single dimension of biodiversity, highlighting the importance of considering multiple aspects of biodiversity in the management of natural ecosystems.</p>
Fig. 2. Consensus trees for the Cyathaspididae. A in A phylogenetic analysis of the heterostracan jawless vertebrate family Cyathaspididae
Fig. 2. Consensus trees for the Cyathaspididae. A, after Lundgren and Blom (2013); B, after Randle and Sansom (2017); C, after Denison (1964). Taxa not used in the analysis in this paper are denoted by an asterisk (*).
figure 2 The dated phylogenetic trees using the cytb gene for G. subgutturosa. Blue bars show 95 in Unraveling goitered gazelle (Gazella subgutturosa) diversification: insights from phylogeography and species distribution modeling
figure 2 The dated phylogenetic trees using the cytb gene for G. subgutturosa. Blue bars show 95% highest posterior density intervals of the estimated node ages; numbers next to the nodes are mean node ages (Mya). The red and green lines show new haplotypes from this study.
Figure 5. Bayesian Inference tree calculated with complete cox1 in Novel phylogenetic clade of avian Haemoproteus parasites (Haemosporida, Haemoproteidae) from Accipitridae raptors, with description of a new Haemoproteus species
Figure 5. Bayesian Inference tree calculated with complete cox1 (1428 bp), cox3 (753 bp), and cytb (1127 bp) sequences of haemosporidian parasites and Klossiella equi (MH203050) and Klossia razorbacki (MT084562) as the outgroup. Bayesian posterior probabilities and Maximum Likelihood bootstrap values are indicated at most nodes. The scale bar indicates the expected number of substitutions per site according to the model of sequence evolution applied.
Figure 3. Phylogenetic tree inferred from cytochrome B in Phlebotomus (Paraphlebotomus) chabaudi and Phlebotomus riouxi: closely related species or synonyms?
Figure 3. Phylogenetic tree inferred from cytochrome B data of Phlebotomus chabaudi and Ph. riouxi specimens. We added to the analysis the sequences of Ph. chabaudi published by Tabbabi et al. (2014). The phylogram results from bootstrapped data sets obtained using the PhyML 3.0 program [21] using GTR (general time reversible) + G distribution (gamma distribution of rates with four rate categories). The tree was visualized using the TreeDyn program, version 198.3 [7]. The percentages above the branches are the frequencies with which a given branch appeared in 500 bootstrap replications. Only bootstrap values higher than 50% on the early branches are shown. A sequence of Ph. sergenti (AF161216) was used as the outgroup. The sequences marked by * were published by Tabbabi et al. (2014); R = sequences found in specimens morphologically characterized as Ph. riouxi. C = sequences found in specimens morphologically characterized as Ph. chabaudi. RC = sequences found in specimens morphologically characterized as Ph. chabaudi or Ph. riouxi. Int = sequences found in specimens morphologically characterized as intermediate between Ph. riouxi and Ph. chabaudi.
Fig.2. The phylogenetic tree for 72 in Genetic Diversity Of (Brassica Napus L.) Spring Oilseed Rape
Fig.2. The phylogenetic tree for 72 individual of Brassica napus constructed on the basis of RAPD data: M - 'Maskot, S - 'Sw Savan', H -'Heros', U -'Ural', L -'Landmark'
Fig. 2b. Phylogenetic tree indicating the Asia-I in Prevalence of a new genetic group, MEAM-K, of the whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) in Karnataka, India, as evident from mtCOI sequences
Fig. 2b. Phylogenetic tree indicating the Asia-I group, which was the most abundant genetic group in this study.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.