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452 results for “Mitogenomics”
Figure 2 in Mitogenomic phylogeny of the Asian colobine genus Trachypithecus with special focus on Trachypithecus phayrei (Blyth, 1847) and description of a new species
Figure 2 Mitogenomic tree showing phylogenetic relationships and divergence times among mitochondrial lineages of Trachypithecus (A) and detailed view on T. phayrei (B) Node bars indicate 95% highest posterior densities (HPDs). Node supports of <100% ML BS and <1.0 BI PP are given at respective nodes. In A, species group assignment is given on the right; *: T. crepusculus, a member of the T. obscurus group according to phenotype and nuclear sequence data. In B, sample labels contain individual ID and sample location number (as in Figures 1, 5, Supplementary Table S1). Clade assignment is given on the right. Complete ultrametric tree including all non-Trachypithecus taxa and details on estimated divergence times are provided in Supplementary Figure S1 and Table S4, respectively.
Figure 1 in Mitogenomic phylogeny of the Asian colobine genus Trachypithecus with special focus on Trachypithecus phayrei (Blyth, 1847) and description of a new species
Figure 1 Distribution of Trachypithecus phayrei according to IUCN Red List (Bleisch et al., 2020) Numbers indicate sample locations for genetic analysis: 1: Letsegan, 2: Kin, 3: Dudaw-Taung, 4: Ramree Island, 5: near Mount Arakan, 6: Mount Popa, 7: 30 miles northwest of Toungoo, 8: Bago Yoma, 9: South Zamayi Reserve, 10: Myogyi Monastery, 11: Panlaung-Pyadalin Cave Wildlife Sanctuary, 12: Mount Yathae Pyan, 13: Yado, 14: Ho Mu Shu Pass, 15: Gaoligong Mountains National Park, 16: Cadu Ciaung, 17: Ngapyinin, 18: Lamaing, 19: Nattaung, 20: Gokteik, and 21: Se'en (for additional information see Supplementary Table S1). Underlined sites refer to type localities of examined holotypes (16: Presbytis melamera, 21: Pithecus shanicus).
SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes
<p>The accurate quantification of eukaryotic species abundances from bulk samples remains a key challenge for community ecology and environmental biomonitoring. We resolve this challenge by combining shotgun sequencing, mapping to reference DNA barcodes or to mitogenomes, and three correction factors: (a) a percent‐coverage threshold to filter out false positives, (b) an internal‐standard DNA spike‐in to correct for stochasticity during sequencing, and (c) technical replicates to correct for stochasticity across sequencing runs. The SPIKEPIPE pipeline achieves a strikingly high accuracy of intraspecific abundance estimates (in terms of DNA mass) from samples of known composition (mapping to barcodes R<sup>2</sup> = .93, mitogenomes R<sup>2</sup> = .95) and a high repeatability across environmental‐sample replicates (barcodes R<sup>2</sup> = .94, mitogenomes R<sup>2</sup> = .93). As proof of concept, we sequence arthropod samples from the High Arctic, systematically collected over 17 years, detecting changes in species richness, species‐specific abundances, and phenology. SPIKEPIPE provides cost‐efficient and reliable quantification of eukaryotic communities.</p>
Complex models of sequence evolution improve fit, but not gene tree discordance, for tetrapod mitogenomes
<p>Variation in gene tree estimates is widely observed in empirical phylogenomic data and is often assumed to be the result of biological processes. However, a recent study using tetrapod mitochondrial genomes to control for biological sources of variation due to their haploid, uniparentally inherited, and non-recombining nature found that levels of discordance among mitochondrial gene trees were comparable to those found in studies that assume only biological sources of variation. Additionally, they found that several of the models of sequence evolution chosen to infer gene trees were doing an inadequate job of fitting the sequence data. These results indicated that significant amounts of gene tree discordance in empirical data may be due to poor fit of sequence evolution models and that more complex and biologically realistic models may be needed. To test how the fit of sequence evolution models relates to gene tree discordance, we analyzed the same mitochondrial datasets as the previous study using two additional, more complex models of sequence evolution that each model a different biologically realistic aspect of the evolutionary process: a covarion model to incorporate heterotachy, and a model partitioned model to incorporate variable evolutionary patterns by codon position. Our results show that both additional models fit the data better than the models used in the previous study, with the covarion being consistently and strongly preferred as tree size increases. However, even these more preferred models still inferred highly discordant mitochondrial gene trees, thus deepening the mystery around what we label the "Mito-Phylo Paradox" and leading us to ask whether the observed variation could be biological after all.</p>
Figure 1 in Mitochondrial genomes of four pierid butterfly species (Lepidoptera: Pieridae) with assessments about Pieridae phylogeny upon multiple mitogenomic datasets
Figure 1. Circular map of Baltia butleri, Talbotia naganum, Pontia callidice, Pontia daplidice mitochondrial genome. COI, COII, and COIII refer to the cytochrome oxidase subunits; CytB refers to cytochrome B; ATP6 and ATP8 refer to subunits 6 and 8 of F0 ATPase; ND1-6 refers to the components of NADH dehydrogenase. The tRNAs locations are marked by the color blocks and labeled by the IUPAC-IUB single letter amino acid code. L1, L2, S1, and S2 denote tRNALeu (CUN), tRNALeu (UUR), tRNASer (AGN), and tRNASer (UCN), respectively. The non-underlined genes are transcribed on the majority strand whereas the underlined genes are transcribed on the minority strand.
Figure 16 in Mitochondrial genomes of four pierid butterfly species (Lepidoptera: Pieridae) with assessments about Pieridae phylogeny upon multiple mitogenomic datasets
Figure 16. Bayesian inference (BI) and Maximum likehood (ML) phylogenetic trees inferred from mitochondrial genomes of pierid family based on 22tRNA genes.
Figure 3 in Mitochondrial genomes of four pierid butterfly species (Lepidoptera: Pieridae) with assessments about Pieridae phylogeny upon multiple mitogenomic datasets
Figure 3. Relative Synonymous Codon Usage (RSCU) of the four pierid butterfly mitogenomes newly determined in this study.
Figure 15 in Mitochondrial genomes of four pierid butterfly species (Lepidoptera: Pieridae) with assessments about Pieridae phylogeny upon multiple mitogenomic datasets
Figure 15. Bayesian inference (BI) and Maximum likehood (ML) phylogenetic trees inferred from mitochondrial genomes of pierid family based on four datasets (13PCGs, 13PCGs+2rRNAs, 2rRNAs, 2rRNAs+22tRNAs).
Supplemental material to the journal article "The complete mitogenome of an unidentified Oikopleura species"
<ul> <li>Wibisana2024)_rev2.tar.gz: aligned sequence files, command-line notes and figures related to the phylogenetic tree in the journal article “The complete mitogenome of an unidentified Oikopleura species”, revision 2.</li> <li>Wibisana2024_rDNA_PacBio_read.fa: a sequence read from the same run used to assemble the mitogenome, that contains a copy of the rDNA locus of the nuclear genome.</li> <li>Wibisana2024_supplementary_rev2.pdf: supplementary figures and tables for the article, revision 2.</li> </ul>
Analyses of the redlegged earth mite mitogenome (Halotydeus destructor: Tucker)
<p>Data and analyses for the paper: </p> <p>Thia et al. (accepted) The mitogenome of <em>Halotydeus destructor</em> (Tucker) and its relationships with other trombidiform mites as inferred from nucleotide sequences and gene arrangements. <em>Ecology and Evolution</em>.</p> <p>In this work, Thia et al. described the first complete mitogenomic sequence of the redlegged earth mite (RLEM). Phylogenetic analyses were used to contextualise the evolutionary relationships of the RLEM mitogenome with those of other mites from the order Trombidiformes. Phylogenies were inferred through Bayesian inference using a combination of nucleotide sequences and gene order arrangements of protein-coding and rRNA genes.</p>
Fig. 1 in First complete mitogenome sequence of Korean Gloydius ussuriensis (Viperidae: Crotalinae)
Fig. 1. Maximum likelihood (ML) phylogenetic tree constructed with 37 viper mitogenomes, based on 13 concatenated protein-coding genes. Achalinus meiguensis (FJ424614) was used as an outgroup species and bootstrap values are shown at the nodes. The mitogenome of Gloydius ussuriensis (OR680782) was determined in this study.
Fig. 6 in Comparative Analysis of Complete Mitogenomes of Two Gobies and Their Phylogenetic Implication.
Fig. 6. Termination-associated sequences (TAS), conserved sequence blocks (CSB-1, CSB-2, and CSB-3) and central conserved sequences (CSB-D) and GTGGG box in control region of two Oxyurichthys species mitogenomes.
Fig. 8 in Comparative Analysis of Complete Mitogenomes of Two Gobies and Their Phylogenetic Implication.
Fig. 8. Phylogenetic trees of goby derived from Maximum Likelihood (ML) method based on 13 PCGs + 2 rRNAs. The numbers at nodes are ultrafast bootstrap values. GenBank accession numbers are placed in front of species names.
Fig. 7 in Comparative Analysis of Complete Mitogenomes of Two Gobies and Their Phylogenetic Implication.
Fig. 7. Phylogenetic trees of goby derived from Bayesian Inference (BI) method based on 13 PCGs + 2 rRNAs. The numbers at nodes are posterior probability values. GenBank accession numbers are placed in front of species names.
Fig. 5 in Comparative Analysis of Complete Mitogenomes of Two Gobies and Their Phylogenetic Implication.
Fig. 5. The putative origin of L-strand replication (OL) of Oxyurichthys ophthalmonema (a) and Oxyurichthys microlepis (b).
Supplemental material to the journal article "Tracing Homopolymers in Oikopleura dioica's mitogenome"
<p>Supplemental material to the journal article “Tracing Homopolymers in <em>Oikopleura dioica</em>’s mitogenome”, consisting of:</p> <ul> <li>The I25 mitochondrial genome (GenBank ID PP146516) and its annotation (not in GenBank)</li> <li>Transcript model sequences used to annotate the genome</li> <li>Nucleotide sequences of<em> cytochrome oxidase I </em>used to compute the tree in Figure 3</li> </ul> <p>Updated on August 6th 2024:</p> <ul> <li>Add raw reads used to assemble the mitogenome.</li> <li>ATP6 gene coordinate corrected (7110 -> 7104) to reach TAA stop codon.</li> </ul>
Fig. 3 in The complete mitogenome of Argas vulgaris (Filippova, 1961) and its phylogenetic status in subgenus Argas (Acari: Argasidae)
Fig. 3. Phylogenetic tree of Argas species based on the 16S rRNA gene contained in the mitochondrial genome. Numbers at the nodes are bootstrap values of the ML analysis. The GenBank accession numbers are listed after the species names.
Fig. 2 in The complete mitogenome of Argas vulgaris (Filippova, 1961) and its phylogenetic status in subgenus Argas (Acari: Argasidae)
Fig. 2. Evolutionary relationships among ticks of the Argasidae families. The phylogenetic tree of complete sequences of mitochondrial genomes. Numbers at the nodes are bootstrap values of the ML analysis. The GenBank accession numbers are listed after the species names.
Fig. 1 in The complete mitogenome of Argas vulgaris (Filippova, 1961) and its phylogenetic status in subgenus Argas (Acari: Argasidae)
Fig. 1. The assembled mitogenome of Argas vulgaris. All the annotated genes are plotted in the outer circle and the inner tract shows the GC content.
Fig. 5 in The complete mitogenome of Argas vulgaris (Filippova, 1961) and its phylogenetic status in subgenus Argas (Acari: Argasidae)
Fig. 5. Key morphological characters of female Ar. vulgaris. (a) Dorsal view of female Ar. vulgaris. (b) Ventral view of female Ar. vulgaris. (c) Posthypostomal seta, ventral view. (d) Details structure of the marginal cells between the dorsal and ventral surfaces. (e) Genital aperture of female Ar. vulgaris. (f) Ventral view of anus location. (g) Ventral view of capitulum. (h) Ventral view of hypostome of the dentition formula.
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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)
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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.