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Fig. 2 in Prey-associated genetic differentiation in two species of silver fly (Diptera: Chamaemyiidae), Leucotaraxis argenticollis and L. piniperda
Fig. 2. Individual-based isolation by distance for eastern and western groups of both Leucotaraxis species. Pairwise genetic distance was calculated as linear genotypic distance and Euclidean geographic distance was calculated from collection site coordinates. Points are differentially shaded for distances between two individuals collected from the same adelgid prey host plant genus (e.g., Tsuga—Tsuga), or for two individuals collected from different adelgid prey host plant genera (e.g., Tsuga—Pinus).
Fig. 1 in Prey-associated genetic differentiation in two species of silver fly (Diptera: Chamaemyiidae), Leucotaraxis argenticollis and L. piniperda
Fig. 1. Maps showing sample sites indicating the host plant genus of the adelgid prey from which flies were collected for: A) L. argenticollis, and B) L. piniperda; and pie charts showing population genetic structure for: C) L. argenticollis, and D) L. piniperda. Structure results correspond to the plots shown in Figs. 3 and 4.
Fig. 5 in Prey-associated genetic differentiation in two species of silver fly (Diptera: Chamaemyiidae), Leucotaraxis argenticollis and L. piniperda
Fig. 5. Haplotype network of Leucotaraxis argenticollis DNA barcode sequences.The area of each pie chart is proportional to the number of samples sharing that haplotype. Small black dots represent unsampled haplotypes. Pie charts indicate the proportions of flies sampled from different host plant genera of adelgid prey.
Simulation code for: Effects of population size change on the genetics of adaptation following an abrupt change in environment
<p>Since the rediscovery of Mendelian genetics over a century ago, there has been much debate about the evolutionary importance of mutations with large phenotypic effects. While population genetic models predict that large-effect mutations will typically contribute to adaptation following an abrupt change in environment, the prediction applies to populations of stable size and overlooks effects of population size change on adaptation (e.g., population decline following habitat loss; growth during range expansion). We evaluate the phenotypic and fitness effects of mutations contributing to adaptation immediately following an abrupt environmental shift that alters both selection and population size dynamics. We show that large-effect mutations are likely to contribute to adaptation in populations declining to a new carrying capacity, somewhat smaller-effect mutations contribute to evolutionary rescue, and small-effect mutations predominate in growing populations. We also show that the relative contributions of positively selected and overdominant mutations to adaptation depend on interactions between the phenotypic effect size distribution for new mutations and the specific form of population size change during adaptation (i.e., growth, decline, or evolutionary rescue). Our results illustrate how population size dynamics can shape the genetic basis of adaptation, which should motivate empirical comparisons of populations adapting in different demographic contexts.</p>
Assessment of genetic diversity, population structure and wolf-dog hybridisation in the Eastern Romanian Carpathian wolf population
<p class="MsoNormal"><span>The Carpathian Mountains were always inhabited by grey wolves and present one of the largest distribution areas in Europe, comprising between 2,300 to 2,700 individuals in Romania. To date, however, relatively little is known about the Romanian wolf population. We aimed to provide a first assessment of genetic diversity, population structure and wolf-dog hybridisation based on 444 mostly non-invasively collected samples in the Eastern Romanian Carpathians. Pack reconstruction and analysis of population genetic parameters were performed with mitochondrial DNA control-region sequencing and microsatellite genotyping. We found relatively high levels of genetic diversity, which is similar to values found in previous studies on Carpathian wolves from Poland and Slovakia, as well as to the long-lasting Dinaric-Balkan wolf population. We found no significant population structure in our study region, suggesting effective dispersal and admixture. Analysis of wolf-dog hybridisation using a Single Nucleotide Polymorphism panel optimised for hybrid detection revealed low rates of admixture between wolves and domestic dogs. Our results provide evidence for the existence of a genetically viable wolf population in the Romanian Carpathians. The genetic data obtained in this study may serve as valuable baseline information for the elaboration of monitoring standards and management plans for wolves in Romania.</span></p>
FIGURE 4 in Relative Genetic Homogeneity within a Phenotypically Diverse group: The Case of Lake Tana Labeobarbus (Cyprinidae) Species Flock, Ethiopia
FIGURE 4. An unrooted Neighbor Joining tree of Lake Tana Labeobarbus species constructed by APE (an R-package) using pair-wise genetic distances among individuals based on analysis of 10 microsatellite loci. Bootstrap percentage values shown at nodes are from 100 pseudo-replicates and indicate the level of support for each group; only bootstrap values higher than 50% are indicated.
FIGURE 3 in Relative Genetic Homogeneity within a Phenotypically Diverse group: The Case of Lake Tana Labeobarbus (Cyprinidae) Species Flock, Ethiopia
FIGURE 3. Scatter plot from Discriminant analysis of Principal Components (DPC; Jombart et al. 2010) of microsatellite data from 161 Lake Tana Labeobarbus individuals. The 95% confidence ellipses of each group based on the common covariance matrix assumption for the multivariate normal distribution are presented. Points represent individual genotypes and symbols represent species (A) or spawning populations (B). A. Using species as grouping factor with asterisks representing the estimated means for each population: Pop A = L. acutirostris, Pop B = L. brevicephalus, Pop C = L. crassibarbus, Pop D = L. gorgorensis, Pop E = L. gorguari, Pop F = L. intermedius, Pop G = L. longissimus, Pop H = L. macrophtalmus, Pop I = L. megastoma, Pop J = L. nedgia, Pop K = L. platydorsus, Pop L = L. surkis, Pop M = L. tsanensis, Pop N = L. truttiformis. B. Using spawning strategy as grouping criteria: ▲riverine spawning population, ●lacustrine spawning population.
FIGURE 2 in Relative Genetic Homogeneity within a Phenotypically Diverse group: The Case of Lake Tana Labeobarbus (Cyprinidae) Species Flock, Ethiopia
FIGURE 2. Bayesian clustering assignment of individuals based on Structure analysis of 10 microsatellite loci of Labeobarbus populations from Lake Tana and adjacent water bodies. A. Analysis of whole dataset without a priori population definitions (K=1–15). B. Lake Tana Labeobarbus populations only with K = 2 inferred clusters. 1. L. acitirostris, 2. L. brevicephalus, 3. L. crassibarbus, 4. L. gorgorensis, 5. L. gorguari, 6. L. longissimus, 7. L. macrophtalmus, 8. L. megastoma, 9. L. nedgia, 10. L. platydorsus, 11. L. surkis, 12. L. truttiformis, 13. L. tsanensis, 14. L. intermedius, 15. L. beso.
FIGURE 1. A in Relative Genetic Homogeneity within a Phenotypically Diverse group: The Case of Lake Tana Labeobarbus (Cyprinidae) Species Flock, Ethiopia
FIGURE 1. A. Map showing major river drainages of Ethiopia; B. Map of Lake Tana. All samples of Lake Tana were drawn from sites (area lying within the red rectangle) located in the Bahir Dar Gulf.
Genetic impacts on DNA methylation help elucidate regulatory genomic processes
<p><strong>Background</strong>: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk.</p> <p><strong>Results</strong>: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2,358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are <em>cis</em>-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1,520 co-localisations across 1,325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as <em>USP1</em> and <em>DOCK7</em> (total cholesterol levels), and <em>ICOSLG</em> (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying <em>cis</em>-meQTLs, (e.g. through disruption of transcription factor binding sites for CTCF and SMC3), and <em>trans</em>-meQTLs (e.g. through regulating the expression of <em>ACD</em> and <em>SENP7 </em>which can modulate DNA methylation at distal sites).</p> <p><strong>Conclusions</strong>: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at <a href="https://epicmeqtl.kcl.ac.uk/">https://epicmeqtl.kcl.ac.uk/</a>.</p>
An evaluation of isolation by distance (IBD) and isolation by resistance (IBR) on genetic structure of the Persian squirrel (Sciurus anomalus) in the Zagros forests of Iran
<p>For conservation of wild species, it is important to understand how landscape change and land management can affect gene flow and movement. Landscape genetic analyses provide a powerful approach to infer effects of various landscape factors on gene flow, thereby informing conservation actions. The Persian squirrel is a keystone species in the woodlands and oak forests of Western Asia, where it has experienced recent habitat loss and fragmentation. We conducted landscape genetic analyses of individuals sampled in the northern Zagros Mountains of Iran (provinces of Kurdistan, Kermanshah, and Ilam), focusing on evaluation of isolation by distance (IBD) and isolation by resistance (IBR), using 16 microsatellite markers. The roles of geographical distance and landscape features including roads, rivers, developed areas, farming and agriculture, forests, lakes, plantation forests, rangelands, shrublands and rocky areas of varying canopy cover, and swamp margins on genetic structure were quantified using individual-based approaches and resistance surface modelling. We found a significant pattern of IBD but only weak support for an effect of forest cover on genetic structure and gene flow. It seems that geographical distance is an important factor limiting the dispersal of the Persian squirrel in this region. The results of the current study inform ongoing conservation programs for the Persian squirrel in the Zagros oak forest.</p>
Online Mendelian Inheritance in Man (OMIM): Comprehensive genetic disorder database for inherited phenotypes and genes
<p><strong>ABSTRACT: </strong></p> <p>Online Mendelian Inheritance in Man (OMIM) is a comprehensive and authoritative research resource that provides curated descriptions of human genes and phenotypes, along with their intricate relationships. I have compiled a dataset that specifically focuses on genes from the Online Mendelian Inheritance in Man database. The dataset includes the unique identifiers (MIM IDs) and names of these OMIM genes.</p> <p><strong>Instructions:</strong></p> <p>Dataset was downloaded and uploaded to excel to have unnecessary columns removed. Then dataset was imported to Jupyter Notebook and further cleaned of the nullified values and unrelated gene types such as phenotypes and etc. A new column with the respective links was added to make a total of 4 columns with one type: genes. Dataset was uploaded to the drg-depot cheaha.</p> <p><strong>Inspiration:</strong></p> <p>This dataset uploaded to U-BRITE for "DRG_DEPOT" summer 2023 team project.</p> <p><strong>Acknowledgements:</strong></p> <p>Joanna S. Amberger, Carol A. Bocchini, François Schiettecatte, Alan F. Scott, Ada Hamosh</p> <p><em>Nucleic Acids Research</em>, Volume 43, Issue D1, 28 January 2015, Pages D789–D798, DOI: <a href="https://doi.org/10.1093/nar/gku1205">https://doi.org/10.1093/nar/gku1205</a></p> <p><strong>OMIM Access to Gene Information:</strong> https://omim.org/search/advanced/entry</p> <p>U-BRITE Last Updated: July 5, 2023</p>
(raw dataset) "Spatial biology of Ising-like synthetic genetic networks"
<p>This is the raw data for the manuscript Simpson et al "Spatial biology of Ising-like synthetic genetic<br> networks"</p>
Citrus genomic resources unravel putative genetic determinants of Huanglongbing pathogenicity
<p>Citrus HLB caused by Candidatus Liberibacter asiaticus is a pathogen-triggered</p> <p>immune disease. Here, we identified putative genetic determinants of HLB</p> <p>pathogenicity by integrating citrus genomic resources to characterize the pan</p> <p>genome of accessions that differ in their response to HLB. Genome-wide associ</p> <p>ation mapping and analysis of allele-specific expression between susceptible,</p> <p>tolerant, and resistant accessions further refined candidates underlying the</p> <p>response to HLB. We first developed a phased diploid assembly of Citrus sinensis</p> <p>‘Newhall’ genome and produced resequencing data for 91 citrus accessions that</p> <p>differ in their response to HLB. These data were combined with previous rese</p> <p>quencing data from 356 accessions for genome-wide association mapping of</p> <p>the HLB response. Genes determinants for HLB pathogenicity were associated</p> <p>with host immune response, ROS production, and antioxidants. Overall, this</p> <p>study has provided a significant resource of citrus genomic data and identified</p> <p>candidate genes to be further explored to understand the genetic determinants</p> <p>of HLB pathogenicity</p>
Genetic variation data derived from ferret transmission experiments of avian H3N8 influenza viruses
<p>Supplementary Dataset 1. Genetic variation data derived from ferret transmission experiment of HN/4-10 virus<br> Supplementary Dataset 2. Genetic variation data derived from ferret transmission experiment of CS/1000 virus<br> Supplementary Dataset 3. Genetic variation data derived from ferret transmission experiment of CK/FE12 virus<br> Supplementary Dataset 4. Genetic variation data derived from ferret transmission experiment of CK/F0316 virus</p>
Data from: Genetic variation at innate and adaptive immune genes - contrasting patterns of differentiation and local adaptation in a wild gull
<p>Immunogenetic variation in natural vertebrate populations is expected to respond to spatial and temporal fluctuations in pathogen assemblages. While spatial heterogeneity in pathogen-driven selection enhances local immunogenetic adaptations and population divergence, different immune genes may yield contrasting responses to the environment. Here, we investigated population differentiation at the key pathogen recognition genes of the innate and adaptive immune system in a colonial bird species, the black headed gull <em>Chroicocephalus ridibundus</em>. We assessed genetic variation at three toll-like receptor (TLR) genes (innate immunity) and the major histocompatibility complex (MHC) class I and II genes (adaptive immunity) in gulls from seven colonies scattered across Poland. As expected, we found much greater polymorphism at the MHC than TLRs. Population differentiation at the MHC class II, but not MHC-I, was significantly stronger than at neutral microsatellite loci, suggesting local adaptation. This could reflect spatial variation in the composition of extra-cellular parasite communities (e.g. helminths), possibly driven by sharp differences in habitat structure between colonies. Despite contrasting patterns of population differentiation, both MHC classes showed similar regimes of diversifying selection. Some significant population differentiation was also observed at TLRs, suggesting that innate immune receptors may respond to fine-scale spatial variation in pathogen pressure, although this pattern could have been enhanced by drift. Our results suggested that local adaptation at the pathogen recognition immune genes can be maintained at relatively small or moderate spatial scales in species with high dispersal potential and highlighted the complexity of immunogenetic responses of animals to heterogeneous environments.</p>
FIGURE 3. Genetic structure between N. lobata and N in Molecular phylogeny and taxonomy of the genus Nanocnide (Urticaceae) with particular attention to the Ryukyu Islands endemic N. lobata
FIGURE 3. Genetic structure between N. lobata and N. pilosa based on averaged MIG-seq data inferred using structure. The sample 1–4 and 5–9 correspond to N. lobata and N. pilosa. More precisely, the numbers correspond to the samples as follows: 1: R2. 2: R9. 3: R10. 4: R19. 5: R23. 6: KY18. 7: 33028. 8: H30528. 9: H30337.
Contrast compositions of kimberlites - genetic conclusions (Kuoyka field, Yakutia)
<p>The compositions (mineralogy, major- and trace-element chemistry of rocks and minerals, as well as Sr-Nd-Hf isotope systematics) of two kimberlite bodies, the Obnazhennaya pipe and the Velikan dyke from the Kuoyka field, Yakutian kimberlite province (YaKP), located close to each other (the distance is 1 km) and having the same Upper Jurassic age. The kimberlites of the two bodies are contrastingly different in composition. The Obnazhennaya pipe is composed of pyroclastic kimberlite of high-Mg, low-Ti of composition, characterized by high saturation of clastic material of the lithospheric mantle (CMLM). Pyroclastic kimberlite contains rare inclusions of coherent kimberlite from previous intrusion phases. The Velikan dyke is represented by coherent kimberlite of relatively high-Fe, high-Ti composition, having neither mantle xenoliths nor olivine xenocrysts. The similarity of isotope-geochemical characteristics for kimberlites of both bodies, and their spatial and temporal proximity suggests that their formation is associated with the presence of a single primary magmatic source located in the asthenosphere. It is assumed that the asthenospheric melt differentiated into two parts: 1) predominantly substantially carbonate composition and 2) carbonate-silicate compositions, which formed respectively 1) high-Mg and 2) Mg-Fe and Fe-Ti petrochemical types of kimberlites. Both parts of the melt had different disintegrating abilities. The higher ability to destroy and subsequently capture CMLM belongs to the melt, which formed a high-Mg type of kimberlite and which, according to the structural-textural classification, more often corresponded to the pyroclastic kimberlite. It has been suggested that the primary kimberlite melt of asthenospheric origin, having a high-Fe, high-Ti composition, is similar to the coherent kimberlite composition from the Velikan dyke (in wt.%: SiO<sub>2</sub> - 21.8, TiO<sub>2</sub> - 3.5, Al<sub>2</sub>O<sub>3</sub> - 4.0, FeO - 10.6, MnO - 0.19, MgO -21.0 , CaO - 17.2, Na<sub>2</sub>O - 0.24, K<sub>2</sub>O - 0.78, P<sub>2</sub>O<sub>5</sub> - 0.99, CO<sub>2</sub> - 12.6). It is concluded that if the pyroclastic kimberlite contains only xenogenic Ol, then a part of the Ol macrocrysts with a high content of FeO in the coherent kimberlite crystallized from the melt. The similarity of the Sr-Nd-Hf isotope systematics and trace element compositions for kimberlites of different ages (from Devonian to Upper Jurassic) in different parts of the YaKP (in Kuoyka, Daldyn and Mirninsky fields) indicates a single long-lived homogeneous magmatic asthenospheric source.</p>
Figure 5 in A revision of the West African freshwater crab genus Afrithelphusa Bott, 1969 (Brachyura: Deckeniidae: Deckeniinae) based on new morphological and genetic data
Figure 5. Afrithelphusa afzelii (Colosi 1924), adult ♂ CW 25.0 mm, ZMB 34607, from Moyamba District, Sierra Leone: a, right cheliped, frontal view; b, left cheliped, frontal view; i, right cheliped carpus superior view; m, right cheliped merus superior view. Afrithelphusa gerhildae Bott, 1969, adult ♂ CW 22.5 mm, SMF 2619a, Le Voile de la Mariée, Kindia, Guinea: c, right cheliped, frontal view (Cumberlidge 1999, fig. 50A); d, left cheliped, frontal view (Cumberlidge 1999, fig. 50A); j, right cheliped carpus superior view; n, right cheliped merus superior view. Afrithelphusa leonensis (Cumberlidge, 1987), adult ♂, CW 26.4 mm, ZMB Crust. 34,606, from Guma Lake, Sugar Loaf Mountain, Sierra Leone: e, right cheliped, frontal view; f, left cheliped, frontal view; k, right cheliped carpus superior view; o, right cheliped merus superior view. Afrithelphusa monodosa (Bott, 1969), adult ♂, CW 24.3 mm, NMU 24.IV.2005, Sarabaya, Guinea: g, right cheliped, frontal view; h, left cheliped, frontal view; l, right cheliped carpus superior view; p, right cheliped merus superior view. Photographs a, b, e, f, i, k, m, o by P. A. Mvogo Ndongo; g, h, l, p by Neil Cumberlidge and Margaret Lorenz; j, n by Michael Türkay. Scale bar: a–h = 11.2 mm; i–p = 5.6 mm. CW = carapace width, ZMB = Museum für Naturkunde, Berlin, Germany, SMF = Senckenberg Museum, Frankfurt, Germany, NMU = Northern Michigan University, USA.
Figure 2 in A revision of the West African freshwater crab genus Afrithelphusa Bott, 1969 (Brachyura: Deckeniidae: Deckeniinae) based on new morphological and genetic data
Figure 2. Afrithelphusa afzelii (Colosi 1924), adult ♂, CW 25.0 mm, ZMB Crust. 34,607, from Moyamba District, Sierra Leone: a, whole animal, dorsal view. Afrithelphusa gerhildae Bott, 1969, adult ♂ CW 22.5 mm, SMF 2619a, Le Voile de la Mariée, Kindia, Guinea: b, whole animal, dorsal view. Afrithelphusa leonensis (Cumberlidge, 1987), adult ♂, CW 26.4 mm, ZMB Crust. 34,606, from Guma Lake, Sugar Loaf Mountain, Sierra Leone: c, whole animal, dorsal view. Afrithelphusa monodosa (Bott, 1969), adult ♂, CW 24.3 mm, NMU 24.IV.2005, Sarabaya, Guinea: d, whole animal, dorsal view. Photographs a, c by PAMN; b by Michael Türkay; d by N. Cumberlidge and M. Lorenz. Scale bar: a = 17.2 mm; b = 15.5 mm; c = 18.9 mm; d = 15.7 mm. CW = carapace width, ZMB = Museum für Naturkunde, Berlin, Germany, SMF = Senckenberg Museum, Frankfurt, Germany, NMU = Northern Michigan University, USA, PAMN = Pierre Armand Mvogo Ndongo.
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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.