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763 results for “Mitochondrial DNA”
Phylogeny of "Philoceanus complex" seabird lice (Phthiraptera: Ischnocera) inferred from mitochondrial DNA sequences
<p>Data from "Phylogeny of “<em>Philoceanus </em>complex” seabird lice (Phthiraptera: Ischnocera) inferred from mitochondrial DNA sequences". See the file index.html for details. Data includes NEXUS files for sequences, tree files output by MrBayes and PAUP, and host-parasite association files for TreeMap.</p>
Inter-Chemical Correlation results for the study: HHEARx2017-1740 (Mitochondrial DNA biomarkers of prenatal metal mixture exposure: intergenerational inheritance and infant growth)
Title: Mitochondrial DNA biomarkers of prenatal metal mixture exposure: intergenerational inheritance and infant growth <br>Species: Homo sapiens <br>Number of samples: 1423 <br>Number of named analytes: 20 <br>Datasource url: https://hheardatacenter.mssm.edu/PublicFile/ViewPublicFile?projectid=19 <br>
Data and software supporting the manuscript 'The population frequency of human mitochondrial DNA variants is highly dependent upon mutational bias'
<p>Next-generation sequencing can quickly reveal genetic variation potentially linked to heritable disease. As databases encompassing human variation continue to expand, rare variants have been of high interest, since the frequency of a variant is expected to be low if the genetic change leads to a loss of fitness or fecundity. However, the use of variant frequency when seeking genomic changes linked to disease remains very challenging. Here, we explore the role of selection in controlling human variant frequency using the HelixMT database, which encompasses hundreds of thousands of mitochondrial DNA (mtDNA) samples. We find that a substantial number of synonymous substitutions, which have no effect on protein sequence, were never encountered in this large study, while many other synonymous changes are found at very low frequencies. Further analyses of human and mammalian mtDNA datasets indicate that the population frequency of synonymous variants is predominantly determined by mutational biases rather than by strong selection acting upon nucleotide choice. Our work has important implications that extend to the interpretation of variant frequency for non-synonymous substitutions. </p> <p> </p>
Figure 1 in Evaluation of the taxonomy of Helix cincta (Muller, 1774) and Helix nucula (Mousson, 1854); insights using mitochondrial DNA sequence data
Figure 1. Map showing the localities of samples used in the present study representing the morphologically defined species and the distribution of Helix cincta (dash line, light grey) and Helix nucula (continuous line, dark grey).
Heteroplasmy Benchmark Dataset - mitochondrial DNA mixture model - MiSeq - U5-H1-M1-M2-M3-M4-M5 - FASTQ
<p>mtDNA mixture model of 2 mtDNA sequences belonging to haplogroups U5 and H1. Run on Illumina MiSeq with 3 different polymerases (Clontech, Herculase, NEB Taq), and different DNA extraction protocols - Paired-end Fastq files</p> <p>M1 = Mixture 1:2 i.e. 50%</p> <p>M2 = Mixture 1:10 i.e. 10%</p> <p>M3 = Mixture 1:50 i.e. 2%</p> <p>M4 = Mixture 1:100 i.e. 1%</p> <p>M5 = Mixture 1:200 i.e. 0.5%</p>
Fig. 7. Maximum-likelihood tree for the mitochondrial DNA gene Cytochrome Oxidase C subunit 1 in A new species of the catfish Neoplecostomus (Loricariidae: Neoplecostominae) from a coastal drainage in southeastern Brazil
Fig. 7. Maximum-likelihood tree for the mitochondrial DNA gene Cytochrome Oxidase C subunit 1 for specimens of Neoplecostomus microps from rio Paraíba do Sul, rio Guapi- Açu and rio Macaé, and of Neoplecostomus paraty, using TN93+G model (n=21). Neoplecostomus paranensis and Neoplecostomus ribeirensis were used as outgroups.
Fig. 2 in Preliminary Report On Mitochondrial Dna Variation In Macaca Fascicularis From Singapore
Fig. 2. Neighbor-joining trees for each of five mtDNA gene fragments including: A, cytochrome b; B, 12s rRNA; C, COI; D, COII; E, COIII. Bootstrap support values are presented at each node.
Fig. 3 in Preliminary Report On Mitochondrial Dna Variation In Macaca Fascicularis From Singapore
Fig. 3. Maximum parsimony trees for each of five mtDNA gene fragments including: A, cytochrome b; B, 12s rRNA; C, COI; D, COII; E, COIII. Bootstrap support values are presented at each node.
Fig. 1 in Preliminary Report On Mitochondrial Dna Variation In Macaca Fascicularis From Singapore
Fig. 1. Map of sample locations within the Bukit Timah (BTNR) and Central Catchment (CCNR) Nature Reserves.
Fig. 3 in Broad Taxon Sampling of Ciliates Using Mitochondrial Small Subunit Ribosomal DNA
Fig. 3. Concatenated mitochondrial and nuclear SSU-rDNA tree inferred from an alignment of 2333 included characters. Most likely ML tree is shown; the BI tree was the same for well-supported nodes. Node support is as in Fig 1.
Fig. 2 in Broad Taxon Sampling of Ciliates Using Mitochondrial Small Subunit Ribosomal DNA
Fig. 2. Nuclear SSU-rDNA tree inferred from an alignment of 1543 included characters. The most likely ML tree is shown; the BI tree was the same for well-supported nodes. Node support is as in Fig 1.
Fig. 1 in Broad Taxon Sampling of Ciliates Using Mitochondrial Small Subunit Ribosomal DNA
Fig. 1. Mitochondrial SSU-rDNA tree inferred from an alignment of 790 included characters. The most likely ML tree is shown; the BI tree was the same for well-supported nodes. Node support is shown as: ML bootstraps/BI posterior probability. Values ≤ 50 are shown as "-".
Fig. 2 in Phylogeography Of The Western Populations Of Stylodipus Telum (Rodentia, Dipodidae) Based On Mitochondrial Dna
Fig. 2. Phylogeographic reconstruction of S. telum based on cytb. BI posterior probability / ML bootstrap support per 1000 replications is indicated at the nodes (only values over 70 % are shown). Photo: S. telum falzfeini from Sagi (Oleshki District) by M. Rusin, 2017-05-17.
Fig. 1 in Phylogeography Of The Western Populations Of Stylodipus Telum (Rodentia, Dipodidae) Based On Mitochondrial Dna
Fig. 1. Sampling localities of S. telum used in the study. White — range of S. telum falzfeini (original unpublished data) and green — range of S. telum turovi (Shenbrot et al., 1995).
Fig. 2. Minimum spanning network for haematozoa mitochondrial DNA cytochrome b in Prevalence and genetic diversity of haematozoa in South American waterfowl and evidence for intercontinental redistribution of parasites by migratory birds
Fig. 2. Minimum spanning network for haematozoa mitochondrial DNA cytochrome b haplotypes detected in South American waterfowl. Shaded circles represent unsampled nodes. All circles are drawn proportional to the frequency at which haplotypes were observed. Lines separating nodes are drawn to scale based on the number of nucleotide mutations, unless otherwise indicated by hash marks. Only haplotypes with a length of 358 bp or greater were included. Haplotype name abbreviations are as follows: Haem = Haemoproteus, Leuc = Leucocytozoon, and Plas = Plasmodium.
Figure 2 in Examining metrics and magnitudes of molecular genetic differentiation used to delimit cetacean subspecies based on mitochondrial DNA control region sequences
Figure 2. Relationship between ΦST and Nei's estimate of net divergence (dA) among cetacean population, subspecies, and species pairs estimated using mitochondrial DNA control region sequence data. Specific values mentioned in the text are numbered: 1 = Neophocaena species; 2 = killer whale populations. The three green squares in the left-hand side of the figure (ΦST <0.07) represent, from bottom to top, the subspecies comparisons for S. attenuata, S. longirostris, and L. obscurus, respectively.
Figure 1 in Examining metrics and magnitudes of molecular genetic differentiation used to delimit cetacean subspecies based on mitochondrial DNA control region sequences
Figure 1. Box and whisker plots showing median and 1st and 3rd quartiles, and minimum and maximum values for six metrics of genetic divergence among cetacean population, subspecies, and species pairs estimated using mitochondrial DNA control region sequence data.
Mitochondrial DNA sequencing results control and MELAS fibroblasts. Povea-Cabello, S. et al 2022.
<p>Mitochondrial DNA sequencing results from control and MELAS patients-derived dermal fibroblasts. Povea-Cabello, S. et al 2022. </p>
Figure 2. A in Mitochondrial Dna Sequence Data Indicate Evidence For Multiple Species Within Peromyscus Maniculatus
Figure 2. A) Phylogenetic tree generated using Bayesian (MrBayes; Huelsenbeck and Ronquist 2001), maximum likelihood (RAxML; Version 8.1.17, Stamatakis 2006), and parsimony methods (PAUP* v. 4.0a165, Swofford 2002) and DNA sequence data from the mitochondrial cytochrome-b gene. The topology depicted is from the Bayesian analysis. Clade probability values (≥ 0.95) for the Bayesian analysis are indicated by an asterisk (*) and are to the left of the first slash, bootstrap values for the maximum likelihood analysis are shown between the two slashes, and bootstrap values obtained from the parsimony analysis are to the right of the last slash. Line at bottom of figure depicts the nucleotide substitution rate per site per million years. B) Same phylogenetic tree as depicted in Figure 2A except unsupported nodes (C, G, and H) were collapsed.
Figure 4. Approximate distributions and associated divergence times for A in Mitochondrial Dna Sequence Data Indicate Evidence For Multiple Species Within Peromyscus Maniculatus
Figure 4. Approximate distributions and associated divergence times for A) Peromyscus maniculatus-like ancestor; B) P. melanotis-like ancestor; C) P. gambelii/keeni/sejugis/sp.-like ancestor; D) P. polionotus-like ancestor; E) P. sonoriensis-like ancestor; F) P. labecula and P. maniculatus - like ancestor; G) P. keeni/sp.-like ancestor; and H) P. keeni-like, P. gambelii-like, P. sejugis-like, and P. sp.-like ancestors. Divergence times were estimated from the BEAST analysis (Version 2.4, Bouckaert et al. 2014) of the mitochondrial cytochrome-b gene dataset (see Fig. 3). Shading schemes that correspond to species distributions are shown in the inset.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.