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1,696 results for “DNA sequences”
Figs 17–19. 17 in Macrocera rohaceki sp. nov. and other interesting records of Keroplatidae (Diptera) from southern and central Europe, with DNA sequence data
Figs 17–19. 17 – habitus of Isoneuromyia pseudochracea (Landrock, 1925); 18 – male of Isoneuromyia czernyi (Strobl, 1909) visiting flower of Chaerophyllum aromaticum (Apiaceae); 19 – female of Isoneuromyia czernyi (Strobl, 1909). (Photos by Jan Ševčík and Michal Tkoč).
Figs 5–10 in Macrocera rohaceki sp. nov. and other interesting records of Keroplatidae (Diptera) from southern and central Europe, with DNA sequence data
Figs 5–10. Isoneuromyia czernyi (Strobl, 1909), male: 5 – wing; 6 – thorax, dorsal view; 7 – habitus; 8 – terminalia, ventral view; 9 – terminalia, dorsal view, tergite 9 removed; 10 – tergite 9 and cerci, external view.
Figs. 1–4 in Copelatus sibelaemontis sp. nov. (Coleoptera: Dytiscidae) from the Moluccas with generic assignment based on morphology and DNA sequence data
Figs. 1–4. Copelatus sibelaemontis sp. nov. 1 – habitus; 2 – median lobe in ventral view; 3 – the same in lateral view; 4 – lateral lobe (paramere).
Fig 1 in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 1. Map of Southeast Asia showing the approximate location of the new (Singapore and Bali) and GenBank sequences included in the study. Numbers correspond to the following locations (haplotype IDs in parentheses): ★, Singapore (Sing1–3); 1, Vietnam (Viet1 & 2); 2, Cambodia (Camb1 & 2); 3, Thailand (Thai1); 4, Thailand (Thai2); 5, Malaysia (Selangor1 & 2); 6, Malaysia (Johor); 7, south Sumatra, Indonesia (Sumatra1 & 2, Java1); 8, Java (Java1); 9, Kalimantan, Borneo (Borneo3); 10, Sarawak, Borneo (Borneo1); 11, Sepilok, Borneo (Borneo2); 12, Bali, Indonesia (Bali1 & 2); 13, Sibuyan, Philippines (Phil1); 14, Bangkok, Thailand (Thai3 & 4); 15, Malaysia (W. Malay); 16, Malaysia (E. Malay2); 17 Malaysia (E. Malay1);18, north Sumatra (Sumatra3–6, 9); 19, west Borneo, Indonesia (Borneo9); 20, west Borneo, Indonesia (Borneo4–7); 21, central Borneo, Indonesia (Borneo4 & 6); 22, Bangka, south Sumatra (Sumatra 7 & 8); 23, Java, Indonesia (Java2 & 3); 24, northeast Borneo, Indonesia (Borneo8); 25, Mindanao, Philippines (Phil2); 26, Timor (Timor). Several Borneo haplotypes appear in multiple locations.
Fig 4. Median-joining haplotype network for M in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 4. Median-joining haplotype network for M. fascicularis. The size of the circular nodes representing haplotypes is proportional to the number of sequences comprising the haplotype. Shading of circular nodes corresponds to general geographic groupings including Sundaic islands (white), mainland Indochina (gray), Malay Peninsula and northern Sumatra (dark gray), and Singapore (black). Haplotype identifications are presented in Table 1.
Fig 3 in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 3. Phylogenetic tree topology from Bayesian inference of 12S/tRNA-val/16S mtDNA sequences using a Birth-Death speciation tree prior, and HYK+G+I nucleotide substitution model in BEAST v2.1.3. Lettered identifications for clades are presented below the branches at major nodes. Posterior probabilities are displayed above the branches at nodes. Numbers in parentheses appearing with haplotype identifications are presented in Table 1, and correspond to numbered locations presented on the Figure 1 map. The Singapore haplotypes form two phylogenetic subgroupings, one from the Bukit Timah Nature Reserve (Sing1) and the other from the Central Catchment Nature Reserve (Sing2 & Sing3).
Fig. 4 in Two new Oriental species of Paramanota Tuomikoski (Diptera: Mycetophilidae), with DNA sequence data
Fig. 4. Molecular affiliation of Paramanota rodzayi based on Maximum likelihood analysis of the combined dataset (12S, 28S, and COI). The numbers below the branches indicate bootstrap support (BS) values above 75.
Fig. 3. Paramanota bifalx Hippa, 2010 in Two new Oriental species of Paramanota Tuomikoski (Diptera: Mycetophilidae), with DNA sequence data
Fig. 3. Paramanota bifalx Hippa, 2010 (Thailand). A, Right half of hypopygium, dorsal view; B, Median lobes and the ventral lobe of gonostylus, dorsal view. Scale bar = 0.1 mm. cm = comb-like row of pale lamellae, cr = cercus, gs d = dorsal lobe of gonostylus, f l = curved finger-like lobe, gs v = ventral lobe of gonostylus, gx = gonocoxa, gx l = ventral gonocoxal lobe, h l = hand-like lobe, hp = hypoproct, tg 9 = tergite 9, tg 10 = tergite 10.
Fig. 1 in Two new Oriental species of Paramanota Tuomikoski (Diptera: Mycetophilidae), with DNA sequence data
Fig. 1. Paramanota rodzayi, new species (holotype). A, Hypopygium, dorsal view; B, Hypopygium, ventral view; C, Ventral and median lobe of gonostylus, anteroventral view; D, Aedeagus with associated structures, dorsal view; E, Antennal flagellomere 4, lateral view. Scale bar = 0.1 mm. cr = cercus, gs d = dorsal lobe of gonostylus, gs m = median lobe of gonostylus, gs v = ventral lobe of gonostylus, gx = gonocoxa, gx l = ventral gonocoxal lobe, hp = hypoproct, tg 9 = tergite 9, tg 10 = tergite 10.
Fig 2 in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 2. Map of central Singapore showing the sampling locations in the Bukit Timah (BTNR) and Central Catchment (CCNR) Nature Reserves. Map created using ArcGIS® (ESRI® 2015).
Fig. 1 in Molecular Systematics of Mouse Opossums (Didelphidae: Marmosa): Assessing Species Limits using Mitochondrial DNA Sequences, with Comments on Phylogenetic Relationships and Biogeography
Fig. 1. Provenance of sequenced specimens of Marmosa (localities of sequenced outgroup specimens are not shown). Numbers refer to entries in the Gazetteer (appendix).
Fig. 3 in Molecular Systematics of Mouse Opossums (Didelphidae: Marmosa): Assessing Species Limits using Mitochondrial DNA Sequences, with Comments on Phylogenetic Relationships and Biogeography
Fig. 3. The maximum-likelihood tree inferred from the best-fit model of nucleotide substitution (table 4). ML bootstrap support values and Bayesian posterior probabilities are indicated above and below branches, respectively. Branch and terminal labels follow the same conventions explained in the caption to figure 2.
Fig. 2 in Molecular Systematics of Mouse Opossums (Didelphidae: Marmosa): Assessing Species Limits using Mitochondrial DNA Sequences, with Comments on Phylogenetic Relationships and Biogeography
Fig. 2. Strict consensus of 96 equally most-parsimonious trees (L 5 2198; CI 5 0.36; RI 5 0.80). Bootstrap support values are indicated above branches subtending species and conspecific haplogroups discussed in the text. For each terminal, country of origin, next-largest political unit (state, department, province, etc.), and an alphanumeric specimen identifier (from table 2) are provided. Numbers in parentheses refer to localities mapped in figure 1 and listed in the Gazetteer (appendix).
FIG. 1 in DNA Sequence Data from the Holotype of Marmosa elegans coquimbensis Tate, 1931 (Mammalia: Didelphidae) Resolve Its Disputed Relationships
FIG. 1. Bayesian phylogenetic tree of Thylamys cytochrome b sequences. Numbers at nodes indicate posterior probabilities (PP). Filled circles at nodes denote PPs equal to 1.0. Unmarked nodes received PPs less than 0.5. Within T. elegans, tips are labeled with country, region, specimen identifier, and, in parentheses, a GenBank accession number. The holotype of Marmosa elegans coquimbensis Tate, 1931, is in boldface type. For other species, tips of the phylogeny are collapsed and the outgroup is not shown. See appendix 1 for a full list of sequences included in the phylogeny. A full tree file corresponding to this topology is available on TreeBase (doi: http://purl.org/phylo/treebase/phylows/study/TB2:S25505).
Fig. 1 in Populations analysis of the Brazilian Sharpnose Shark Rhizoprionodon lalandii (Chondrichthyes: Carcharhinidae) on the São Paulo coast, Southern Brazil: inferences from mt DNA sequences
Fig. 1. Median-joining haplotype network. The haplotypes are represented by circles, with the width proportional to their frequencies. Black circles correspond to Praia Grande, white to Ubatuba, and gray to Itanhaém samples. Each branch corresponds to a single mutation, except line a (with 2 mutations) and line b (with 3 mutations).
Figure 2. Phylogenetic relationships among the 29 in Molecular phylogeny and phylogeography of the Greek populations of the genus Orthometopon (Isopoda, Oniscidea) based on mitochondrial DNA sequences
Figure 2. Phylogenetic relationships among the 29 specimens of Orthometopon species. Individuals from two other terrestrial isopod species were used as outgroup taxa: Ligidium sp. and Armadillidium vulgare. Phylogenetic analyses, maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI), all produced trees with the same topology. Only the BI tree is presented here. Numbers above the branches indicate bootstrap values in the MP and ML analyses, respectively (MP/ML). Numbers below the branches indicate the posterior probabilities of the Bayesian analysis (BI).
Figure 1 in Molecular phylogeny and phylogeography of the Greek populations of the genus Orthometopon (Isopoda, Oniscidea) based on mitochondrial DNA sequences
Figure 1. Map showing the sampling localities of the 29 specimens used for the DNA analysis. The numbers correspond to those listed in Table 1.
The hsp65 metabarcoding DNA sequence database for taxonomic allocations using the Mothur (Version 1.0.0)
<ul> <li>The <em>hsp65</em> gene codes for an Heat Shock Protein (Telenti et al., 1993) and is widespread in the Actinobacteria phylum. It is well suited for the species allocation of the Nocardia genus (Rodriguez-Nava et al., 2006).</li> <li>The <em>hsp65</em> database, named ACTIhsp65, was designed to apply the <em>hsp65</em>-metabarcoding analytical scheme published in Vautrin et al. (2021). It includes the full <em>hsp65</em> identifiers, GenBank accession numbers, complete taxonomic records (domain down to strain code) of about 401 nucleotide-long <em>hsp65</em> sequences of 1066 unique taxa belonging to 198 genera.</li> <li>Nucleotide sequences of <em>hsp65</em> (range: 165-565 nucleotides) were either retrieved from public repositories (GenBank) or made available by Veronica Rodriguez-Nava.Vautrin et al. (2021) described the PCR and high throughput Illumina Miseq DNA sequencing procedures used to produce <em>hsp65</em> sequences.</li> <li>ACTIhsp65 V1.0.0 (June 2018 release) is made available under the Creative Commons Attribution 4.0 International Licence. It can be used for the taxonomic allocations of <em>hsp65 </em>sequences down to the species.</li> </ul>
Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies
<p><span>Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding datasets, therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences in Molecular Operational Taxonomic Units (MOTUs), each of which ideally representing a homogeneous taxonomic entity, e.g. a species or a genus. However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for nine markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g. Insecta, Oligochaeta). Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of over-splitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96-0.99) are generally appropriate, while more specific markers require lower values (0.85-0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate a careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.</span></p>
Pooled DNA sequencing to identify SNPs associated with a major QTL for bacterial wilt resistance in Italian ryegrass (Lolium multiflorum Lam.)
<p>We used pooled DNA sequencing to characterize a major QTL for bacterial wilt resistance of Italian ryegrass and to develop inexpensive sequence-based markers to efficiently target resistance alleles for marker-assisted recurrent selection. From the mapping population segregating for the QTL, DNA of 44 of the most resistant and 44 of the most susceptible F<sub>1</sub> individuals were pooled and sequenced using the Illumina HiSeq2000 platform. Allele frequencies of 18 x 10<sup>6</sup> single nucleotide polymorphisms (SNP) were determined in the resistant and susceptible pool. A total of 271 SNPs on 140 scaffold sequences of the reference parental genome showed significantly different allele frequencies in both pools. We converted 44 selected SNPs to KASP markers, genetically mapped these proximal to the major QTL and thus validated their association with bacterial wilt resistance.</p>
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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.