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129 results for “phylogenetic comparative analysis”
Comparative analysis of chloroplast genomes of Sanguisorba species and insights into phylogenetic implications and molecular dating
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Data from: The evolution of reproductive diversity in Afrobatrachia: a phylogenetic comparative analysis of an extensive radiation of African frogs
The reproductive modes of anurans (frogs and toads) are the most diverse of terrestrial vertebrates, and a major challenge is identifying selective factors that promote the evolution or retention of reproductive modes across clades. Terrestrialized anuran breeding strategies have evolved repeatedly from the plesiomorphic fully aquatic reproductive mode, a process thought to occur through intermediate reproductive stages. Several selective forces have been proposed for the evolution of terrestrialized reproductive traits, but factors such as water systems and co-evolution with ecomorphologies have not been investigated. We examined these topics in a comparative phylogenetic framework using Afrobatrachian frogs, an ecologically and reproductively diverse clade representing more than half of the total frog diversity found in Africa (∼400 species). We infer direct development has evolved twice independently from terrestrialized reproductive modes involving subterranean or terrestrial oviposition, supporting evolution through intermediate stages. We also detect associations between specific ecomorphologies and oviposition sites, and demonstrate arboreal species exhibit an overall shift towards using lentic water systems for breeding. These results indicate that changes in microhabitat use associated with ecomorphology, which allow access to novel sites for reproductive behavior, oviposition, or larval development, may also promote reproductive mode diversity in anurans.
Comparative mitochondrial genome and phylogenetic analysis of malaria mosquitoes Anopheles hyrcanus and Anopheles messeae supplementary files
<p><strong>T</strong><strong><span>able</span></strong><strong> S1.</strong> This study encompassed 105 species, along with their corresponding taxonomy and GenBank registration numbers.</p> <p><strong>Figure S1</strong> Inferred secondary structures of tRNAs in the mt genome of <em>An. </em><em><span>h</span></em><em>yrcanus</em><em> </em><span>(A)</span><em> </em><span>and </span><em>An. </em><em><span>m</span></em><em>esseae</em><em> </em><span>(B)</span>, with corresponding amino acids labeled next to the tRNAs.</p>
Comparative Analysis of Complete Chloroplast Genomes of 13 Species in Epilobium, Circaea, and Chamaenerion and Insights into Phylogenetic Relationships of Onagraceae
<p>This is all the alignments which used to constructed a phylogenetic tree in our study about Onagraceae. The evening primrose family, Onagraceae, is a well defined family of the order Myrtales, which comprises 22 genera widely distributed from boreal to tropical areas. In the present study, we report and characterize the complete chloroplast genome sequences of 13 species in <em>Circaea</em>,<em> Chamaenerion</em>, and <em>Epilobium</em> using a next-generation sequencing method. We also retrieved plastome sequences from two other Onagraceae genera to characterize the chloroplast genome of the family. The complete plastomes of Onagraceae showed a typical quadripartite structure and encoded an identical set of 112 genes (with exclusion of duplication), including 78 protein-coding genes, 30 transfer RNAs, and four ribosomal RNAs. The results show that chloroplast genomes are basically conserved in gene arrangement across the family. Whereas, a large segment of inversion was detected in the LSC region of all samples in the<em> Oenothera </em>subsect. <em>Oenothera</em>. An inverted repeat (IR) contraction was found in <em>Circaea</em> and<em> Ludwigia </em>samples. We also compared chloroplast genomes across the Onagraceae samples and revealed similarities in some features, including nucleotide content, codon usage, RNA editing sites, and simple sequence repeats (SSRs). Phylogeny was inferred by the chloroplast genome data using maximum-likelihood (ML) and Bayesian inference (BI) methods. The generic relationship of Onagraceae was well resolved by the complete plastome sequences, showing potential value in inferring phylogeny within the family. <em>Oenothera </em>phylogeny was better resolved than other densely sampled genera. Biparental transmission may be the main cause of higher variation in the genus<em> Oenothera</em>.</p>
FIGURE 12 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 12. Ultragryllacris pulchra rubricapitis Bin & Bian, 2021. A. habitus in lateral view; B–E. tegmina in dorsal view: B, D. left tegmen, C, E. right tegmen; A–C. male; D–E. female.
FIGURE 11 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 11. Ultragryllacris pulchra rubricapitis Bin & Bian, 2021. Female: A. head in frontal view; B–C. head and pronotum: B. dorsal view, C. lateral view; D. second and third abdominal tergites in lateral view; E–G. apex of abdomen: E. dorsal view, F. lateral view, G. ventral view; H. apices of ovipositor in lateral view.
FIGURE 8 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 8. NJ tree constructed based on cob genes. ABGD method is indicated with dark gray bars and jMOTU with light gray bars.
FIGURE 4. The secondary structures for 22 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 4. The secondary structures for 22 tRNA genes of the Ultragryllacris pulchra rubricapitis XZ273.
FIGURE 10 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 10. Ultragryllacris pulchra rubricapitis Bin & Bian, 2021. Male: A–B. head in frontal view; C–E. head and pronotum: C–D. dorsal view, E. lateral view; F–G, I. apex of abdomen: F. lateral view, G. apico-dorsal view, I. ventral view; H. ninth abdominal tergite in ventral view.
FIGURE 3. The secondary structures for 22 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 3. The secondary structures for 22 tRNA genes of the Ultragryllacris pulchra rubricapitis XZ267.
FIGURE 7 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 7. NJ tree constructed based on cox1 genes. ABGD method is indicated with dark gray bars and jMOTU with light gray bars.
FIGURE 5. The secondary structures for 22 in Comparative mitogenome analysis and phylogenetic inference of the genus Ultragryllacris (Orthoptera: Gryllacrididae)
FIGURE 5. The secondary structures for 22 tRNA genes of the Ultragryllacris pulchra rubricapitis XZ506.
Why are telomeres the length that they are? Insight from a phylogenetic comparative analysis
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Data from: The evolution of reproductive diversity in Afrobatrachia: a phylogenetic comparative analysis of an extensive radiation of African frogs
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Data from: Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein-Uhlenbeck model
Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and more detailed evolutionary hypotheses, including adaptive hypotheses with multiple selective optima and hypotheses with rate variation within and across lineages. The statistical performance of these sophisticated models has received relatively little systematic attention, however. We conducted an extensive simulation study to quantify the statistical properties of a class of models toward the simpler end of the spectrum that model phenotypic evolution using Ornstein–Uhlenbeck processes. We focused on identifying where, how, and why these methods break down so that users can apply them with greater understanding of their strengths and weaknesses. Our analysis identifies three key determinants of performance: a discriminability ratio, a signal-to-noise ratio, and the number of taxa sampled. Interestingly, we find that model-selection power can be high even in regions that were previously thought to be difficult, such as when tree size is small. On the other hand, we find that model parameters are in many circumstances difficult to estimate accurately, indicating a relative paucity of information in the data relative to these parameters. Nevertheless, we note that accurate model selection is often possible when parameters are only weakly identified. Our results have implications for more sophisticated methods inasmuch as the latter are generalizations of the case we study.
Supplementary material 1 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
COI sequences of Corydoras aeneus and C. paleatus Tables S1–S4, Figs S1–S4
Figure 2 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
Figure 2 K2P genetic distance a nucleotide diversity b Ka/Ks ratio c analyses of protein-coding genes among the eleven Corydoras mitogenomes.
Figure 3 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
Figure 3 Phylogenetic trees of 44 Siluriformes species using concatenated nucleotide sequences of 13 protein-coding genes and two rRNAs using the maximum likelihood method. Numbers in the ML tree represent SH-aLRT support/ultrafast bootstrap support values.
Figure 4 from: Sun C-H, Huang Q, Zeng X-S, Li S, Zhang X-L, Zhang Y-N, Liao J, Lu C-H, Han B-P, Zhang Q (2022) Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. ZooKeys 1083: 89-107. https://doi.org/10.3897/zookeys.1083.76887
Figure 4 Phylogenetic tree of 44 Siluriformes species using concatenated nucleotide sequences of 13 protein-coding genes and two rRNAs via the Bayesian interference method. Applicable posterior probability values are shown.
Figure 9 from: Chen Z-T (2022) Comparative mitogenomic analysis of two earwigs (Insecta, Dermaptera) and the preliminary phylogenetic implications. ZooKeys 1087: 105-122. https://doi.org/10.3897/zookeys.1087.78998
Figure 9 Predicted structural elements in the control regions of Challia fletcheri, Euborellia arcanum, Eudohrnia metallica, and Paratimomenus flavocapitatus.
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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.