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48 results for “DNA alignment”
DNA alignment and resulting bayesian trees of Epithelantha and sister species
<p><span> The use of environmental variables to explain the evolution of lineages has gained relevance in recent studies. Additionally, it has allowed the recognition of species by adding more characters to morphological and molecular information. This study focuses on identifying environmental and landscape variables that have acted as barriers that could have influenced the evolution of <i>Epithelantha</i> species and its close genera.</span></p> <p><span>Our results show that soil pH, isothermality, temperature seasonality, and annual precipitation have a significant phylogenetic signal for <i>Epithelantha</i>. Soil type and landforms are also relevant as ecological barriers that maintain the identity of <i>Epithelantha</i> species.</span></p> <p><span>The variables associated with the soil (pH) have influenced the evolution of <i>Epithelantha</i> and probably in other genera of Cactaceae. Additionally, <i>Epithelantha</i> is frequent in the piedmont and haplic kastanozems. Bioclimatic variables reinforce the recognition of <i>E. micromeris</i> and <i>E. cryptica</i> as independent species. Therefore, ecology can be considered as a factor to explain the high level of endemism in Cactaceae.</span></p>
Data for: Alignments of chloroplast DNA and ITS of tribe Adonideae
<p><span>The Euro-Siberian steppe flora consists of warm- and cold-adapted species, which may have responded differently to Pleistocene glacials and interglacials. Genotyping-by-sequencing individuals from across the distribution range of the pheasant's eye (<em>Adonis vernalis</em>), we aimed to gain insight into steppe florogenesis based on the species' evolutionary history. Although the primary area of origin of the species group comprising <em>A. vernalis</em>, <em>A. villosa</em> and <em>A. volgensis</em> is in Asia, our results indicate that <em>A. vernalis</em> itself is not of Asian origin but evolved in southern (incl. Southeastern) Europe during the Pleistocene, with Spanish populations being clearly genetically distinct<a> </a></span><span>from the Southeastern European populations. We inferred<a> </a></span><span>that <em>A. vernalis</em> migrated eastwards from the sub-Mediterranean forest-steppes of Southeastern Europe into the continental forest-steppe zone. Eastern European populations</span><span> had the highest private allelic richness, indicating long-term large population sizes in this region. As a thermophilic species, <em>A. vernalis</em> seems unlikely to have survived in the cold deserts of the Last Glacial Maximum in Western Siberia, so this region was likely</span><span> (re)colonized postglacially. Overall, our results reinforce the importance of identifying the area of origin and the corresponding ecological requirements of steppe plants in order to understand the composition of today's steppe flora.</span></p>
Aligned and curated mtDNA sequences from: Ancient DNA of narrow-headed voles reveals common features of the Late Pleistocene population dynamics in cold-adapted small mammals
<p><span>Narrow-headed vole, together with collared lemming and common vole, was the most abundant small mammal species across Eurasian Late Pleistocene steppe-tundra environments. Previous ancient DNA studies of </span><span>the latter</span><span> </span><span>two</span><span> revealed dynamic past population histories shaped by climatic fluctuations. To investigate the extent to which species with similar adaptations share common evolutionary </span><span>histories,</span><span> we generated a dataset comprising mitochondrial genomes of 139 ancient and 6 modern narrow-headed voles from multiple sites across Europe and north-</span><span>western</span><span> Asia and covering the last ca. 100 thousand years (ka). We inferred Bayesian time-aware phylogenies using 11 </span><span>radiocarbon-dated</span><span> samples for calibration of the molecular clock. We found that across the three </span><span>species,</span><span> divergence of the main mtDNA lineages occurred during Marine Isotope Stages (MIS) 7 and MIS 5, suggesting a common response </span><span>of species adapted to open habitat to the interglacial environments. </span><span>In European narrow-headed voles, we identified multiple </span><span>time-structured</span><span> mtDNA lineages, implying lineage turnovers. Timing of some of these turnovers was synchronous across all three </span><span>species,</span><span> allowing us to identify the main drivers of the Late Pleistocene dynamics of steppe- and cold-adapted species.</span></p>
Aligned DNA sequence matrix for phylogenetic analyses in the article "A new species of spiny-backed tree frog, genus Osteocephalus (Anura: Hylidae), from the Yanachaga Chemillén National Park in central Peru"
<p>Aligned DNA sequence matrix for phylogenetic analyses of the article "Systematics of Huicundomantis, a new subgenus of Pristimantis (Anura, Strabomantidae) with extraordinary cryptic diversity and eleven new species"</p> <p>The matrix is in NEXUS format and has 14791 bp and 38 terminals.</p> <p>Partitions are as follows:</p> <p>charset 12S_16S = 1-2442;<br> charset mtGenome_other_genes = 2443-9180; charset nonCoding = 3132- 3138 4776- 4857 5203- 5214;<br> charset codonPos1 = 2443-3130\3 3139-4774\3 4858-5200\3 5215-9178\3;<br> charset codonPos2 = 2444-3131\3 3140-4775\3 4859-5201\3 5216-9179\3;<br> charset codonPos3 = 2445-3129\3 3141-4773\3 4860-5202\3 5217-9180\3;<br> charset 16S_ND1nonCoding = 9181- 9428 10390- 10506 ;<br> charset 16S_ND1codonPos1 = 9429-10389\3;<br> charset 16S_ND1codonPos2 = 9430-10387\3;<br> charset 16S_ND1codonPos3 = 9431-10388\3;<br> charset POMCcodonPos1 = 10507-11068\3;<br> charset POMCcodonPos2 = 10508-11066\3;<br> charset POMCcodonPos3 = 10509-11067\3;<br> charset CO1codonPos1 = 11069-12608\3;<br> charset CO1codonPos2 = 11070-12609\3;<br> charset CO1codonPos3 = 11071-12610\3;<br> charset CytbcodonPos1 = 12611-13757\3;<br> charset CytbcodonPos2 = 12612-13758\3;<br> charset CytbcodonPos3 = 12613-13759\3;<br> charset ND2codonPos1 = 13760-14789\3;<br> charset ND2codonPos2 = 13761-14790\3;<br> charset ND2codonPos3 = 13762-14791\3;</p>
DNA alignments for MSc Thesis, University of Edinburgh.
<p>DNA alignments compiled for MSc Thesis, University of Edinburgh. Myanmar Ancestral Area Reconstruction.</p>
DNA sequences of transgenes detected via environmental DNA (raw ABI files, processed FASTA files, and reference alignments)
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Data for: Alignments of chloroplast DNA and ITS of tribe Adonideae
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Aligned and curated mtDNA sequences from: Ancient DNA of narrow-headed voles reveals common features of the Late Pleistocene population dynamics in cold-adapted small mammals
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Aligned DNA sequence matrix for phylogenetic analyses in the article "Fifty years after: a taxonomic revision of the amphibian species from the Ecuadorian biodiversity hotspot Abra de Zamora, with description of two new Pristimantis species"
<p>The aligned matrices are in fasta format. Genes are arranged as follows:</p> <p>Subgenus Huicundomantis (Huicundomantis.fas):</p> <p>12S = 1–905</p> <p>16S = 906–1820</p> <p>RAG-1 = 1821–2463</p> <p> </p> <p>Genus Lynchius (Lynchius.fas):</p> <p>12S = 1–1028</p> <p>16S = 1029–2313</p> <p>RAG-1 = 2314–2925</p> <p> </p> <p>Pristimantis orestes group (Pristimantis_orestes.fas):</p> <p>12S = 1–964</p> <p>16S = 965–2041</p> <p>RAG-1 = 2042–2683</p>
Multiple alignment of DNA-B sequences from EACMV, EACMKV, EACMMV, EACMZV, SACMV (5 "species")
<p>All sequences available in GenBank as of 2019-06-03 were downloaded via the Taxonomy Browser interface. Sequence names were normalized/simplified and orientations of these circular sequences were standardized to begin at the replication origin nick site. Sequences were aligned with MUSCLE and alignments were adjusted with SeAl (A. Rambaut) and AliView (A. Larsson).</p> <p>These results are described in a paper by Crespo-Bellido et al. (2021) https://doi.org/10.1128/JVI.00541-21</p>
Multiple alignment of ICMV and SLCMV DNA-B sequences
<p>All sequences available in GenBank as of 2019-06-03 were downloaded via the Taxonomy Browser interface. Sequence names were normalized/simplified and orientations of these circular sequences were standardized to begin at the replication origin nick site. Sequences were aligned with MUSCLE and alignments were adjusted with SeAl and AliView.</p> <p>Note added 2020-09-07: AJ575821 is listed in the file as ICMV based on its assignment in the NCBI Taxonomy database (taxa 341701 and 31600) but it is better classified as SLCMV.</p> <p>These results are described in a paper by Crespo-Bellido et al. (2021) https://doi.org/10.1128/JVI.00541-21</p>
Multiple sequence alignment of DNA-A sequences from ACMBFV, ACMV, CMMGV, EACMCV, EACMKV, EACMMV, EACMV, EACMZV, SACMV, ICMV, SLCMV (11 species)
<p>All full-length DNA-A sequences available in GenBank as of July 2019 were downloaded via the Taxonomy Browser interface. Sequence names were normalized/simplified and orientations of these circular sequences were standardized to begin at the replication origin nick site. Sequences were aligned with MUSCLE and alignments were manually adjusted with SeAl (A. Rambaut) and AliView (A. Larsson).</p>
Supplementary material 2 from: Nugent CM, Adamowicz SJ (2020) Alignment-free classification of COI DNA barcode data with the Python package Alfie. Metabarcoding and Metagenomics 4: e55815. https://doi.org/10.3897/mbmg.4.55815
File S2 – Python script for custom grid search of hyperparameters for optimization of the neural network
Supplementary material 3 from: Nugent CM, Adamowicz SJ (2020) Alignment-free classification of COI DNA barcode data with the Python package Alfie. Metabarcoding and Metagenomics 4: e55815. https://doi.org/10.3897/mbmg.4.55815
File S3 – The parameters utilized in the grid search for each of the five machine learning algorithms tested in the design of the Alfie package
Supplementary material 4 from: Nugent CM, Adamowicz SJ (2020) Alignment-free classification of COI DNA barcode data with the Python package Alfie. Metabarcoding and Metagenomics 4: e55815. https://doi.org/10.3897/mbmg.4.55815
File S4 – Jupyter notebook with tutorial demonstrating how to apply the Alfie classifier in the Python programming language, and how to train custom alignment-free classifiers using the Alfie training module
Pereira et al snakeworms DNA alignment Supplementary_File_1.nex
<p>Pereira et al snakeworms DNA alignment Supplementary File 1 </p>
Aligned DNA sequence matrix for phylogenetic analyses in the article "Systematics of the Dendropsophus leucophyllatus species group (Anura, Hylidae) from the Chocó region of Ecuador, with description of a new species"
<p>Aligned DNA sequence matrix for phylogenetic analyses of the article "Systematics of the <em>Dendropsophus leucophyllatus</em> species group (Anura, Hylidae) from the Chocó region of Ecuador, with description of a new species"</p> <p>The matrix is in NEXUS format and has 7691 bp and 203 terminals.</p> <p>Partitions are as follows:</p> <div> <div>charset 12S = 1-996;</div> <div> </div> <div>charset CO1codonPos1 = 997-1639\3;</div> <div>charset CO1codonPos2 = 998-1640\3;</div> <div>charset CO1codonPos3 = 999-1638\3;</div> <div> </div> <div>charset ND1nonCoding = 1641- 1713 2675- 2796 ;</div> <div>charset ND1codonPos1 = 1714-2674\3;</div> <div>charset ND1codonPos2 = 1715-2672\3;</div> <div>charset ND1codonPos3 = 1716-2673\3;</div> <div> </div> <div>charset CytbcodonPos1 = 2798-3686\3;</div> <div>charset CytbcodonPos2 = 2799-3687\3;</div> <div>charset CytbcodonPos3 = 2797-3685\3;</div> <div> </div> <div>charset RhodcodonPos1 = 3689-4001\3;</div> <div>charset RhodcodonPos2 = 3690-4002\3;</div> <div>charset RhodcodonPos3 = 3688-4003\3;</div> <div> </div> <div>charset TYRcodonPos1 = 4005-4539\3;</div> <div>charset TYRcodonPos2 = 4006-4537\3;</div> <div>charset TYRcodonPos3 = 4004-4538\3;</div> <div> </div> <div>charset RAG1codonPos1 = 4542-4965\3;</div> <div>charset RAG1codonPos2 = 4540-4966\3;</div> <div>charset RAG1codonPos3 = 4541-4964\3;</div> <div> </div> <div>charset POMCcodonPos1 = 4967-5441\3;</div> <div>charset POMCcodonPos2 = 4968-5439\3;</div> <div>charset POMCcodonPos3 = 4969-5440\3;</div> <div> </div> <div>charset SIAH1codonPos1 = 5443-5836\3;</div> <div>charset SIAH1codonPos2 = 5444-5837\3;</div> <div>charset SIAH1codonPos3 = 5442-5838\3;</div> <div> </div> <div>charset 16S_rec = 5839-7695;</div> </div>
Aligned DNA sequences of Vanilla
<p><strong><span>Premise</span></strong></p> <p><span>Although vanilla is one of the best-known spices, there is a limited understanding of its biology and genetics within Mexico, where its cultivation originated and where phenotypic variability is high. This study aims to augment our understanding of vanilla's genetic resources by assessing species delimitation and genetic, geographic, and climatic variability within Mexican cultivated vanilla. </span></p> <p><strong><span>Methods</span></strong></p> <p><span>Nuclear and plastid DNA sequence data from 58 Mexican samples collected from three regions and 133 <em>ex-situ</em> accessions were used to assess species monophyly using phylogenetic analyses and genetic distances. Intra-specific genetic variation was summarized through the identification of haplotypes. Within the primarily cultivated species, <em>V. planifolia</em>, haplotype relationships were further verified using plastome and rRNA gene sequences. Climatic niche and haplotype composition were assessed across the landscape.</span></p> <p><strong><span>Key Results</span></strong></p> <p><span>Three species (<em>Vanilla planifolia</em>, <em>V. pompona</em>, and <em>V. insignis</em>) and 13 haplotypes were identified among Mexican vanilla. Within <em>V. planifolia</em> haplotypes, hard phylogenetic incongruences between plastid and nuclear sequences suggest past hybridization events. Eight haplotypes exclusively consisted of Mexican samples. The dominant <em>V. planifolia</em> haplotype occurred throughout all three regions as well as outside of its country of origin. Haplotype richness was found to be highest in regions around Papantla and La Chinantla.</span></p> <p><strong><span>Conclusions</span></strong></p> <p><span>Long histories of regional cultivation support the consideration of endemic haplotypes as landraces shaped by adaptation to local conditions and/or hybridization. Results may aid further genomic investigations of vanilla's genetic resources and ultimately support the preservation of genetic diversity within the economically important crop.</span></p>
Aligned and curated mtDNA sequences from: Ancient DNA reveals interstadials as a driver of common vole population dynamics during the last glacial period
<p><strong><span>Aim: </span></strong><span>Many species experienced population turnover and local extinction during the Late Pleistocene. In the case of megafauna, it remains challenging to disentangle climate change and the activities of Palaeolithic hunter-gatherers as the main cause. In contrast, the impact of humans on rodent populations </span><span>is likely to be negligible. This study investigated which climatic and/or environmental factors affect the population dynamics of the common vole. </span><span>This temperate rodent is widespread across Europe and was one of the most abundant small mammal species throughout the Late Pleistocene.</span></p> <p><span><strong>Location:</strong> </span><span>Europe</span></p> <p><strong><span>Taxon: </span></strong><span>Common vole (<em>Microtus arvalis</em>)</span></p> <p><strong><span>Methods: </span></strong><span>We generated a dataset comprised of a 4.2-kb-long fragment of mitochondrial DNA (mtDNA) from 148 ancient and 51 modern specimens sampled from multiple localities across Europe and covering the last 60 thousand years (ka). We used Bayesian inference to reconstruct their phylogenetic relationships and to estimate the age of the specimens that were not directly dated.</span></p> <p><span><strong>Results:</strong> </span><span>We estimated the time to the most recent common ancestor of all last glacial and extant common vole lineages to be 90 ka ago and the divergence of the main mtDNA lineages present in extant populations to between 55 and 40 ka ago, which is earlier than previous estimates. </span><span>We detected several lineage turnovers in Europe during the period of high climate variability at the end of Marine Isotope Stage 3 (MIS 3; 57–29 ka ago) in addition to those found previously around the Pleistocene/Holocene transition.</span><span> </span><span>In contrast, data from the Western Carpathians suggest continuity throughout the Last Glacial Maximum (LGM), even at high latitudes.</span></p> <p><strong><span>Main conclusions: </span></strong><span>The main factor affecting the common vole populations during the last glacial period was the decrease in open habitat during the interstadials, whereas </span><span>climate </span><span>deterioration </span><span>during</span><span> the LGM had little impact on population dynamics. This suggests that the rapid environmental change rather than other factors was the major force shaping the histories of the Late Pleistocene faunas.</span></p>
Aligned DNA sequence matrix for phylogenetic analyses in the article "Molecular and Morphological Assessment of Rain Frogs in the Pristimantis orestes Species Group (Amphibia: Anura: Strabomantidae) with the Description of Three New Cryptic Species from Southern Ecuador"
<p>The aligned matrix is in fasta format. Genes are arranged as follows:</p> <p>12S = 1–901</p> <p>16S = 902–2094</p> <p>RAG-1 = 2095–2733</p>
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Allen Brain Atlas
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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.