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15,277 results for “GENETICS”
Figure 1 in Comparative genetic differentiation study of three coexisting mangrove crabs in western Atlantic
Figure 1. Map showing the sampling sites for Aratus pisonii along the western Atlantic, with collection localities (circles) inside each designated population (dashed areas – names indicated). Different colours represent different populations. States and/or countries of each locality are indicated. For each population, the number of sequences obtained for both mtDNA COI and 16S rDNA genes is indicated. Details of the localities sampled are reported in Table 1. Abbreviations of States: Mexico: CC: Campeche; VZ: Veracruz; TC: Tabasco; TS: Tamaulipas; YN: Yucatán; Brazil: AP: Amapá; PA: Pará; MA: Maranhão; CE: Ceará; RN: Rio Grande do Norte; PE: Pernambuco; AL: Alagoas; BA: Bahia; ES: Espírito Santo; RJ: Rio de Janeiro; SP: São Paulo; PR: Paraná; SC: Santa Catarina.
Figure 5 in Comparative genetic differentiation study of three coexisting mangrove crabs in western Atlantic
Figure 5. Leptuca thayeri. Median-Joining haplotype network for mtDNA COI (a) and 16S rDNA (b), showing the distribution of the haplotypes (H); the circle size is proportional to the haplotype frequency; black circles indicate the median vector; different colours represent different populations; dashed circles indicate suggested isolated geographic regions. (c) Bayesian analysis for genetic differentiation for mtDNA COI among populations.
Figure 4 in Comparative genetic differentiation study of three coexisting mangrove crabs in western Atlantic
Figure 4. Aratus pisonii. Median-Joining haplotype network for mtDNA COI (a) and 16S rDNA (b), showing the distribution of the haplotypes (H); the circle size is proportional to the haplotype frequency; black circles indicate the median vector; different colours represent different populations; dashed circles indicate suggested isolated geographic regions. (c) Bayesian analysis for genetic differentiation for mtDNA COI among populations.
Figure 7 in Comparative genetic differentiation study of three coexisting mangrove crabs in western Atlantic
Figure 7. Mismatch distribution for mtDNA COI of respective clades I (a), II (b), and III (c) of Aratus pisonii; clades I (d), and II (e) of Leptuca thayeri; and for all samples of Goniopsis cruentata (f), showing the frequency of distribution of the number of pairwise nucleotide differences among all individuals, under the sudden expansion model. Columns show the observed frequency distribution and the lines represent the simulated values under the sudden expansion model. Statistics for SSD and HRI with probability values are indicated.
Fig. 1 in Genetic Variability ofDigitonthophagus gazella(F.) (Coleoptera: Scarabaeidae) from Vieques, Puerto Rico and South Africa
Fig. 1. Genetic variation of two populations of Digitonthophagus gazella as indicated by the number of markers scored plotted against coefficient of variation values. A high number of markers decrease the coefficient of variation. More than 93% of genetic variation is encompassed by the markers used.
Figure 2 in Mitogenomics and the genetic differentiation of contemporary Balaena mysticetus (Cetacea) from Svalbard
Figure 2. Bayesian skyline plot illustrating the temporal changes in the genetic diversity of mitogenomes in Svalbard population bowhead whales. The top of the figure illustrates the time in years before present when using the 95% HPD interval of the estimated divergence time for the calculation of µ.
Figure 7 in Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters
Figure 7. Geographical distribution of tridentate Euglossa dilemma sp. nov. (black) and predominantly bidentate Euglossa viridissima (white) as inferred from recent baiting assays (circles) as well as museum material (diamonds). Note lack of E. viridissima in the south-eastern part (Costa Rica) of the range. Museum material included paratypes of E. dilemma and additional specimens of one or both species in the collections of D. W. Roubik, T. Eltz (CTE), G. Gerlach (CGG), the Zoologische Staatssammlung München (ZSM), the Smithsonian Institution (SI), and the Snow Entomological Collection (SEC). Only unambiguous and non-redundant localities were plotted. Localities of baiting assays are (from west to east): Chamela (Jalisco, Mexico), El Chote (Veracruz, Mexico), Ayozinthepec (Oaxaca, Mexico), Monte Pio and Poza Azul (both Veracruz, Mexico), Tuxtla Gutiérrez, Esquintla, Tapachula, Ocosingo and Palenque (all Chiapas, Mexico), Atasta (Campeche, Mexico), Retalhuleu (Guatemala), Lacanjá (Chiapas, Mexico), Escarcega (Campeche, Mexico), El Remate (Campeche, Mexico), Chablekal, Xmatkuil (Yucatán, Mexico), Tikal (Guatemala), San Crisanto (Yucatán, Mexico), Chetumal and Coba (both Quintana Roo, Mexico), Chinandega, Chacocente, Escameca Grande, Jinotega, Ometepe and Las Pampas (all Nicaragua), and Area de Conservación Guanacaste (Costa Rica).
Figure 6 in Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters
Figure 6. Chronogram showing divergence times and phylogenetic relationships of selected lineages in the genus Euglossa and the sibling species Euglossa dilemma sp. nov. and E. viridissima. The tree topology corresponds to that obtained via Bayesian methods. Bayesian posterior probabilities and parsimony bootstrap values are shown for the sister species only. Divergence times were obtained via penalized likelihood using the fossil-calibrated molecular clock procedures described in Ramírez et al. (2010b). The maximum and minimum age estimates for the MRCA of E. dilemma and E. viridissima correspond to the molecular clock analyses in which the MRCA of the genus Euglossa was assigned a fossil calibration of 20 and 15 Myr, respectively.
Figure 2 in Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters
Figure 2. Allele size distribution of Euglossa viridissima- like males from the Yucatán peninsula, Mexico, at the microsatellite locus ann02. Overall, bidentate males (grey bars) had significantly smaller allele sizes than tridentate individuals (black bars), and there was little overlap in allele size. The seven individuals indicated as red circles were also tridentate, but had been clustered with bidentate males in the analysis of perfume similarity (see Fig. 1), lacking HNDB. These seven individuals had the third (central) mandibular tooth significantly displaced towards the tip of the mandible (nearer to the distal tooth, see Fig. 3B), unlike in other tridentate males. Their ann02 allele size suggests that they in fact belong to the bidentate lineage. See text for further explanation.
Figure 4 in Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters
Figure 4. Results of a PCA of 15 morphological variables measured in male Euglossa viridissima and Euglossa dilemma sp. nov. Components 1 and 3, which showed significant differences between the species, are used for this two-dimensional representation. Note that E. dilemma shows slightly less variability and is essentially nested within E. viridissima morphospace. Centroids of distributions are shown.
Figure 3. A in Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters
Figure 3. A, Euglossa viridissima-like males attracted to a bait dish at Xmatkuil, Yucatán, Mexico. B, mandibular morphology of males of tridentate Euglossa dilemma sp. nov., and tridentate and bidentate males of E. viridissima. The position of the central mandibular tooth in tridentate individuals is expressed as the ratio of the distance between the distal and the central tooth to the distance between the central and the basal tooth. Means and standard deviations are given.
Figure 1 in Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters
Figure 1. Differences in the chemical composition of tibial perfumes between tridentate (black circles) and bidentate (grey circles) Euglossa viridissima-like males as revealed by a multidimensional scaling (MDS) analysis. Only tridentate males contained HNDB. Tridentate males without HNDB are highlighted (red symbols).
Figs. 1–4. Ischyomius hovorei, n in Fig. 3 in Genetic Control of Color Polymorphism in the Stag Beetle Cyclommatus metallifer Boisduval (Coleoptera: Lucanidae)
Figs. 1–4. Ischyomius hovorei, n. sp. 1) habitus of male holotype; 2) aedeagus; 3) middle tarsus, dorsal; 4) outline of pronotum, dorsal. Scale bar for fig. 1 5 5 mm; for figs. 2–3 5 0.5 mm.
Fig. 4. A–H in Fig. 3 in Genetic Control of Color Polymorphism in the Stag Beetle Cyclommatus metallifer Boisduval (Coleoptera: Lucanidae)
Fig. 4. A–H, male genitalia of Sapotes. Reference lines to the left of figures equal to 0.5 mm. A. dorsal view of median lobe of S. sordidus; B. lateral view of median lobe of S. sordidus; C. dorsal view of spiculum gastrale of S. sordidus; D. phallobase of S. sordidus; E. dorsal view of median lobe of S. setosus; F. lateral view of median lobe of S. setosus; G. dorsal view of spiculum gastrale of S. setosus; H. phallobase of S. setosus.
Fig. 3. A–J in Fig. 3 in Genetic Control of Color Polymorphism in the Stag Beetle Cyclommatus metallifer Boisduval (Coleoptera: Lucanidae)
Fig. 3. A–J, habitus of species of Sapotes. A. lateral view of male S. sordidus (4.46 mm); B. dorsal view of male S. sordidus; C. lateral view of male S. setosus (3.36 mm); D. dorsal view of male S. setosus; E. lateral view of female S. caseyi (4.32 mm); F. dorsal view of female S. caseyi; G. lateral view of female S. puncticollis (5.09 mm); H. dorsal view of female S. puncticollis; I. lateral view of female S. longipilis (5.04 mm); J. dorsal view of female S. longipilis.
Fig. 2. A–E in Fig. 3 in Genetic Control of Color Polymorphism in the Stag Beetle Cyclommatus metallifer Boisduval (Coleoptera: Lucanidae)
Fig. 2. A–E. Size and arrangement of teeth on inner margin of protibia of species of Sapotes: A. S. longipilis; B. S. puncticollis; C. S. caseyi; D. S. setosus; E. S. sordidus.
Fig. 1. A in Fig. 3 in Genetic Control of Color Polymorphism in the Stag Beetle Cyclommatus metallifer Boisduval (Coleoptera: Lucanidae)
Fig. 1. A) rostrum of Sapotes longipilis showing medial sulcus and arching lateral sulci. B–C, sexual dimorphism in elytral declivity of Sapotes sordidus: B) elytral declivity of male S. sordidus; C) elytral declivity of female S. sordidus.
Fig. 5. A–I in Fig. 3 in Genetic Control of Color Polymorphism in the Stag Beetle Cyclommatus metallifer Boisduval (Coleoptera: Lucanidae)
Fig. 5. A–I, male and female genitalia of Sapotes. Reference line to the right of figures equal to 0.5 mm. A–B. apical portion of male median lobe of S. longipilis; A. dorsal and B. lateral view. C. ovipositor of S. caseyi. D. sternum 8 of S. caseyi. E–I, spermathecae of Sapotes species, with length from tip of arm to ducts: E. S. puncticollis (0.27 mm); F. S. longipilis (0.35 mm); G. S. caseyi (0.30 mm); H. S. sordidus (0.28 mm); I. S setosus (0.23 mm).
Genetic regulatory effects in response to a high cholesterol, high fat diet in baboons
<p>Disease-associated loci discovered through genome-wide association studies (GWAS) are primarily located in non-coding regions with putative regulatory effects on gene expression. Steady-state, standard expression quantitative trait loci (eQTLs) explain only a limited portion of GWAS signals, while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Here, we characterized gene-by-diet effects in a baboon model system. By analyzing three tissue types obtained from 99 captive baboons, we identify hundreds of diet-responsive eQTLs with high tissue specificity. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs of genes associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the dynamic complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using the baboon model.</p>
Data Source file for manuscript: Within-host genetic diversity of extended-spectrum beta-lactamase-producing Enterobacterales in long-term colonized patients
<p>ABSTRACT</p><p>Infections caused by extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales (ESBL-PE) are associated with excess morbidity and mortality. Despite recognition of this immediate impact on human health, essential aspects of their molecular epidemiology remain under-investigated. This includes knowledge on the potential of a particular strain to persist in a host, mutational events during colonization, and the genetic diversity in individual patients over time. To investigate long-term genetic diversity of colonizing and infecting ESBL-producing <i>Klebsiella pneumoniae </i>species complex and ESBL-<i>Escherichia coli</i> in individual patients over time, we conducted performed a ten-year longitudinal retrospective study and extracted clinical and microbiological data from electronic health records. In this investigation, 76 ESBL-<i>K. pneumoniae</i> species complex and 284 ESBL-<i>E. coli</i> isolates were recovered from 19 and 61 patients. Strain persistence was detected in all patients colonized with ESBL-<i>K. pneumoniae </i>species complex, and 83.6% of patients colonized with ES BL-<i>E. coli</i>. Antimicrobial resistance genes, plasmid replicons, and whole ESBL-plasmids were shared between isolates regardless of chromosomal relatedness. Our study suggests that patients colonized with ESBL-producers may act as durable reservoirs for ongoing transmission of ESBLs, and that they are at a prolonged risk of recurrent infection with colonizing strains.</p><p>DATA SOURCE FILE</p><p>In this Data Source file, you will find access to the raw data, metadata and results obtained during the study: "Within-host genetic diversity of extended-spectrum beta-lactamase-producing Enterobacterales in long-term colonized patients". Data is organized following the structure of Figures/Tables of the manuscript and Supplementary Material. Additional figures not included in the main manuscript nor in the Supplementary Material are also available.</p><p>All sequencing and sample data from this study can be accessed at the NCBI database under the BioProject number PRJNA910977: <a href="http://dataview.ncbi.nlm.nih.gov/object/PRJNA910977">http://dataview.ncbi.nlm.nih.gov/object/PRJNA910977. </a>No new software was developed during this study. Standard bioinformatics software was used and the commands used can be accessed at the Supplementary Information file.</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.