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Fig. 3 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 3. Phylogenetic analysis of SSU-rRNA sequence data (aligned over 2035 positions) to infer the relationships of recognised Blastocystis subtypes (STs) as well as new STs discovered in the present study. The tree was constructed using Bayesian Inference method (MrBayes) and used Proteromonas lacertae as an outgroup. Posterior probabilities less than 0.95% are not displayed. The two novel subtypes and additional ST13 and ST24 sequences are indicated in bold. After the present analysis was completed, Santín et al. (2023) reported a subdivision of "ST10" into four STs (i.e. ST10, ST42, ST43 and ST44).
Fig. 2 in Marked genetic diversity within Blastocystis in Australian wildlife revealed using a next generation sequencing-phylogenetic approach
Fig. 2. Diagram of the method used to obtain sequence for a SSU-rRNA gene region (~1750 bp) of Blastocystis. Two primer sets were used to obtain overlapping sequences for this region.
Fig. 1 in Geographic Distribution and Genetic Structures of the Tideland Snails and in Taiwan and Japan.
Fig. 1. Sampling sites of Pirenella nipponica and P. asiatica. Sampling at Japanese sites was carried out in the previous study (Kojima et al. 2006). Areas shown in the pie graphs reflect the number of collected individuals. Black and white sectors in the pie graphs indicate relative frequencies of P. nipponica and P. asiatica.
Fig. 2. A in Geographic Distribution and Genetic Structures of the Tideland Snails and in Taiwan and Japan.
Fig. 2. A statistical parsimony haplotype network of Pirenella nipponica (a) and P. asiatica (b) based on nucleotide sequences of the mitochondrial cytochrome c oxidase subunit I (COI) gene. The areas of the circles are proportional to the frequency of the occurrence of the haplotypes. Numbers of haplotypes are same as those in table 2 and Kojima et al. (2006). Colors of sections denote the relative occurrence frequency of individuals collected in each area. The haplotypes that were not detected in the sample are indicated by small black circles.
Fig. 4 in Phylogeography and Genetic Structure of the Bush Cricket (Orthoptera, Tettigoniidae) in Southern China.
Fig. 4. Structure clustering results. (A) the posterior probability of each K; (B) the distribution of Delta K values; (C) Bayesian clustering results at K = 9; S1–3 was the groups defined by SOMOVA.
Fig. 3. The genetic distances among populations. A in Phylogeography and Genetic Structure of the Bush Cricket (Orthoptera, Tettigoniidae) in Southern China.
Fig. 3. The genetic distances among populations. A: based on Kimura's 2-parameter; B: based on Tamura 3-parameter.
Fig. 2 in Phylogeography and Genetic Structure of the Bush Cricket (Orthoptera, Tettigoniidae) in Southern China.
Fig. 2. Potential distribution areas of D. fissa in different periods. Potential areas for (A) Current day; (B), Last Glacial Maximum; (C), MidHolocene; (D), year 2070 (RCP 4.5).
Fig. 9 in Phylogeography and Genetic Structure of the Bush Cricket (Orthoptera, Tettigoniidae) in Southern China.
Fig. 9. The dispersed path of D. fissa. A: Central China; B: South China; C: Yunnan-Guizhou Plateau; D: Southeast coastal area; E: Sichuan Basin.
Fig. 7 in Phylogeography and Genetic Structure of the Bush Cricket (Orthoptera, Tettigoniidae) in Southern China.
Fig. 7. Mismatch distributions (left) and Bayesian skyline plots (right) for lineages I, IV, and V of D. fissa based on mitochondrial data.
Fig. 6 in Phylogeography and Genetic Structure of the Bush Cricket (Orthoptera, Tettigoniidae) in Southern China.
Fig. 6. The mitochondrial haplotype network of concatenated sequences. The dotted box represents the five lineages based on divergence time analysis.
Fig. 3 in Fig. 3 in Genetic Structure of the Mangrove Killifish Costa, 2011 (Cyprinodontiformes: Aplocheiloidei) Supports A Wide Connection among its Populations.
Fig. 3. Haplotype network of the Kryptolebias marmoratus species group. Maps represent the distribution of each group.
Fig. 2 in Fig. 3 in Genetic Structure of the Mangrove Killifish Costa, 2011 (Cyprinodontiformes: Aplocheiloidei) Supports A Wide Connection among its Populations.
Fig. 2. Distribution of K. hermaphroditus: Orange star indicates type locality; and Green circles indicate recorded localities for the species (Costa 2011; 2016; Sarmento-Soares et al. 2014; Lira et al. 2015; Berbel-Filho et al. 2016; Guimarães-Costa et al. 2017; Tatarenkov et al. 2017a; This study).
Fig. 1 in Fig. 3 in Genetic Structure of the Mangrove Killifish Costa, 2011 (Cyprinodontiformes: Aplocheiloidei) Supports A Wide Connection among its Populations.
Fig. 1. Kryptolebias hermaphroditus from Tutóia, Maranhão State, Delta do Parnaíba, north eastern Brazil; UFRJ12666: A: Hermaphrodite, 35.5 mm SL; B: Male, 20.3 mm SL; C: Male, 28.9 mm SL.
Fig. 1. Circular Bayesian tree inferred from mtDNA cox-2 in Temporal stability of parasite distribution and genetic variability values of Contracaecum osculatum sp. D and C. osculatum sp. E (Nematoda: Anisakidae) from fish of the Ross Sea (Antarctica)
Fig. 1. Circular Bayesian tree inferred from mtDNA cox-2 sequences obtained from specimens of C. osculatum sp. D and C. osculatum sp. E analysed in the present study, based on Bayesian Inference (BI) method using MrBayes v3.2.2 (Ronquist et al., 2012). Evolutionary distance was estimated using the TrN + G (G = 0.60) substitution model as implemented in jModeltest (Posada, 2008), with the AIC approach (Posada and Buckley, 2004). Posterior probability values are the result of 1.000000 of runs and are reported at the nodes. The coloured icons correspond to the two species considered in this study (red = C. osculatum sp. D and blue = C. osculatum sp. E).
Fig. 2 in Temporal stability of parasite distribution and genetic variability values of Contracaecum osculatum sp. D and C. osculatum sp. E (Nematoda: Anisakidae) from fish of the Ross Sea (Antarctica)
Fig. 2. Schematic distribution of the fish species examined in the present study for larval of C. osculatum sp. D and C. osculatum sp. E, along the continental shelf of the Ross Sea coastal ecosystem. Arrows indicating preferred preys and the diet preference for each fish species are reported according to the literature (La Mesa et al., 2004). The represented pelagic organisms comprise species of euphausiids and fish juveniles, benthic and epibenthic organisms are polychaetes, amphipods, decapods and gastropods. A pie chart with the relative proportions of C. osculatum sp. D and C. osculatum sp. E is given for each fish species. Squares and circles represent the hypothetical distribution of C. osculatum sp. D and C. osculatum sp. E larvae in their intermediate hosts.
Fig. 3 in Temporal stability of parasite distribution and genetic variability values of Contracaecum osculatum sp. D and C. osculatum sp. E (Nematoda: Anisakidae) from fish of the Ross Sea (Antarctica)
Fig. 3. Schematic representation of the hypothetic life-cycle of C. osculatum sp. D (a) and C. osculatum sp. E (b) in the Ross Sea.
Fig. 3 in Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds
Fig. 3. Bayesian phylogenetic tree of haemosporidian mtDNA cytochrome b haplotypes isolated from Alaskan grouse and ptarmigan species. Node tips are labeled with abbreviation for parasite genus (Haem = Haemoproteus, Leuc = Leucocytozoon, and Plas = Plasmodium), followed by the lineage name, GenBank accession number for each lineage, and avian (Phas = Phasianidae, Anat = Anatiade, Turd = Turdidae, Paru = Parulidae, Scol = Scolopacidae, Embe = Emberizidae, and Frin = Fringillidae) or invertebrate (Simu = Simuliidae) host family. All haplotypes identified in this study are highlighted in red and asterisks following tip labels indicate a lineage that was isolated from Alaskan bird hosts. Numbers on branches indicate posterior probabilities from our analysis. All reference sequences were obtained from the National Center for Biotechnology Information website or the MalAvi database. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 2. Minimum spanning network for haemosporidian mtDNA cytochrome b in Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds
Fig. 2. Minimum spanning network for haemosporidian mtDNA cytochrome b haplotypes isolated from Alaskan grouse and ptarmigan species. Dark circles represent un-sampled nodes. All circles are proportional to the frequency at which the haplotypes were detected. Lines between nodes are drawn to scale based on the number of nucleotide mutations unless otherwise indicated by hash marks.
Fig. 1 in Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds
Fig. 1. Map of Alaskan sampling regions assembled from multiple game management units and sub-units. Regions were grouped for analysis of haemosporidian prevalence as follows: southcoastal (Kenai Peninsula and southeastern Alaska; GMUs 1C, 1D, 2, 7, 15A, 15B, and 15C), southcentral (Anchorage area and Matanuska-Susitna Valley; GMUs 13A, 13D, 14A, 14C, 16A, and 16B), southwestern (Bristol Bay, Alaska Peninsula, and eastern Aleutian islands; 9D, 9E, and 17C), southern interior (south side of Alaska Range; GMUs 12, 13B, and 13E), northern interior (north side of Alaska Range; GMUs 20A-20E and 25C), and Seward Peninsula (GMU 22C).
Fig. 2 Maximum likelihood phylogenetic tree constructed using the mitochondrial cox1 gene for 103 in Genetic diversity and population genetics of large lungworms (Dictyocaulus, Nematoda) in wild deer in Hungary
ƒFig. 2 Maximum likelihood phylogenetic tree constructed using the mitochondrial cox1 gene for 103 Dictyocaulus lungworms originating from Hungary and five lungworms from GenBank indicated by their accession numbers (one dictyocaulid worm of red deer in New Zealand and four sequences of D. viviparus). Lungworms were collected from hunted deer (fallow, red and roe deer), indicated by triangle, square and circle, respectively. Geographical collecting regions are indicated for each sample
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.