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886 results for “genetic analysis”
Fig. 3 in A multi-approach analysis of the genetic diversity in populations of Astyanax aff. bimaculatus Linnaeus, 1758 (Teleostei: Characidae) from Northeastern Brazil
Fig. 3. Giemsa-stained karyotypes of Astyanax aff. bimaculatus (2n = 50, FN = 96) from sites A (a), B (b) and C (c). In (d), a somatic metaphase after silver nitrate staining in a specimen from Contas River, showing four positive signals (arrows). The bar equals 5µm.
Fig. 2 in A multi-approach analysis of the genetic diversity in populations of Astyanax aff. bimaculatus Linnaeus, 1758 (Teleostei: Characidae) from Northeastern Brazil
Fig. 2. Partial view of collection sites of Astyanax aff. bimaculatus in the State of Bahia, Brazil: (a) Contas River, upstream Pedra Dam, Porto Alegre County – site A, (b) Contas River, downstream Pedra Dam, city of Jequié – site B, and (c) Mineiro stream, Recôncavo Sul Basin, city of Itamari – site C. In (d), view of Pedra Dam reservoir in Middle Contas River, city of Jequié.
Fig. 1 in A multi-approach analysis of the genetic diversity in populations of Astyanax aff. bimaculatus Linnaeus, 1758 (Teleostei: Characidae) from Northeastern Brazil
Fig. 1. Map of the studied area in the State of Bahia, Brazil, showing the hydrographic system and collection sites of Astyanax aff. bimaculatus: (a) site A - Contas River, upstream of Pedra Dam, Porto Alegre County (b) site B - Contas River, downstream of Pedra Dam, city of Jequié (Contas River Basin), (c) site C - Mineiro stream, city of Itamari (Recôncavo Sul Basin) and (*) location of Pedra Dam in Contas River. A specimen of Astyanax aff. bimaculatus is illustrated in detail (total length = 6.65 cm).
Figure 9 in Genets and 'genet-like' taxa (Carnivora, Viverrinae): phylogenetic analysis, systematics and biogeographic implications
Figure 9. Illustration of the phylogenetic relationships within the subfamily Viverrinae obtained here in; civet by courtesy of Delachaux & Niestlé (Dorst & Dandelot, 1976); Genetta johnstoni, Osbornictis, Poiana and Genetta spp. by courtesy of Academic Press (Kingdon, 1997)]
Figure 1 in Genets and 'genet-like' taxa (Carnivora, Viverrinae): phylogenetic analysis, systematics and biogeographic implications
Figure 1. Phylogenetic relationships of the extant carnivores according to Gregory & Hellman (1939; modified).
Figure 3 in Genets and 'genet-like' taxa (Carnivora, Viverrinae): phylogenetic analysis, systematics and biogeographic implications
Figure 3. Illustration of some ultrastructural hair characters (Ex indicates coding related to the intergeneric analysis; In indicates coding related to the intrageneric analysis). A: Cross-section of the GH1 spatula base of Genetta genetta (1) and Genetta abyssinica (2). B: GH1 medullar structure of Genetta genetta (1), Genetta johnstoni (2), Poiana richardsonii (3) and Viverricula indica (4). C: GH1 middle part of the spatula of Poiana richardsonii (1), Osbornictis piscivora (2), Nandinia binotata (3) and Genetta tigrina (4).
Figure 2 in Genets and 'genet-like' taxa (Carnivora, Viverrinae): phylogenetic analysis, systematics and biogeographic implications
Figure 2. Illustration of some cranial and plantar characters (Ex indicates coding related to the intergeneric analysis; In indicates coding related to the intrageneric analysis). A: Skull of Felis silvestris. B: Skull of Poiana richardsonii (Allen, 1924; by courtesy of the American Museum of Natural History). C: Skull of Genetta victoriae (Allen, 1924; by courtesy of the American Museum of Natural History). D: Skull of Osbornictis piscivora (Allen, 1924; by courtesy of the American Museum of Natural History). E: Skull of Genetta genetta (Rosevear, 1974; by courtesy of The Natural History Museum, London). F: Left hindfoot and forefoot of Genetta pardina (Allen, 1924; by courtesy of the American Museum of Natural History). G: Left hindfoot and forefoot of Civettictis civetta (Pocock, 1915; by courtesy of Cambridge University Press).
Data from: Genetic effects of anthropogenic habitat fragmentation on remnant animal and plant populations: a meta-analysis
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Data from: Population analysis reveals genetic structure of an invasive agricultural thrips pest related to invasion of greenhouses and suitable climatic space
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Supplementary materials for Phylogenomics and genetic analysis of solvent-producing Clostridium species
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BIMAGES: Bivalve images for morphological analysis and genetic estimation study
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Data of "Investigating the potential for genetic improvement of nitrogen and phosphorus efficiency of in a Swiss Large White pigs population using chemical analysis"
<p>Data for article 'Investigating the Potential for Genetic Improvement of Nitrogen and Phosphorus Efficiency in a Swiss Large White Pig Population using Chemical Analysis' (DOI: 10.1111/JBG.12472). Dataset of 294 Swiss Large White pigs for which phenotypes of nitrogen efficiency, phosphorus efficiency (both determined by chemical analysis of N and P content of empty body and carcass as well as the feed ingested over the experiment phase), average daily gain and gain:feed ratio are available. We also provide the pedigree that was used to estimate genetic parameters in animal models and a description of the variables (metadata).</p>
Data from: Genetic analysis of Boletus edulis suggests that intra-specific competition may reduce local genetic diversity as a woodland ages
<p>Ectomycorrhizal fungi are key players in terrestrial ecosystems yet their mating systems and population dynamics remain poorly understood. We investigated the fine-scale relatedness structure and genetic diversity of Boletus edulis, one of the world's most commercially important wild mushrooms. Microsatellite genotyping of fruiting bodies from 14 different sites around Bielefeld in Germany revealed little in the way of population structure over a geographic scale of several kilometers. However, on a more local scale we found evidence for elevated relatedness as well as inbreeding. We also observed a significant negative association between the genetic diversity of fruit and the age of the trees under which they were sampled. Taken together, our results suggest that as genets mature, they compete and potentially create conditions under which further spores struggle to become established. By implication, even though this species is widely picked, propagules remain common enough to create strong competition when new habitats become available.</p>
Mixed-stock analysis using Rapture genotyping to evaluate stock-specific exploitation of a walleye population despite weak genetic structure
<p>Mixed-stock analyses using genetic markers have informed fisheries management in cases where strong genetic differentiation occurs among local spawning populations, yet many fisheries are supported by multiple spawning stocks that are weakly differentiated. Freshwater fisheries exemplify this problem, with many harvested populations supported by multiple stocks of young evolutionary age and that are isolated across small spatial scales. As a result, attempts to conduct genetic mixed-stock analyses of inland fisheries have often been unsuccessful. Advances in genomic sequencing now offer the ability to discriminate among populations with weak population structure, by providing the necessary resolution to conduct mixed-stock assignment among previously indistinguishable stocks. We demonstrate the use of genomic data to conduct a mixed-stock analysis of Lake Erie's commercial and recreational walleye (<em>Sander vitreus</em>) fisheries and estimate the relative harvest of weakly differentiated stocks. We used RAD-capture (Rapture) to sequence and genotype individuals at 12,081 loci that had been previously determined to be capable of discriminating between western and eastern basin stocks (mean pairwise F<sub>ST</sub> = 0.001) with 95% reassignment accuracy. An outcome not possible in the past with microsatellite markers. Genetic assignment of 1,075 fish harvested from recreational and commercial fisheries in the eastern basin indicated that western basin stocks supported the majority of the harvest during peak harvest (July – September). Composition of harvest changed seasonally, with eastern basin fish comprising much of the early season harvest (May – June). Clear spatial structure in stock-specific harvest existed; more easterly sites contained more individuals of east basin origin than did westerly sites. Our study provides important stock contribution estimates for Lake Erie fishery management and demonstrates the power of genomic data to facilitate mixed-stock analysis in exploited fish populations with weak population structure or limited existing genetic resources.</p>
Does genetic diversity protect host populations from parasites? A meta-analysis across natural and agricultural systems
<p>If parasites transmit more readily between closely related hosts, then parasite burdens should decrease with increased genetic diversity of host populations. This important hypothesis is often accepted at face value - notorious epidemics of crop monocultures testify to the vulnerability of host populations that have been purged of diversity. Yet the relationship between genetic diversity and parasitism likely varies across contexts, differing between crop and non-crop hosts and between experimental and natural host populations. Here, we used a meta-analytic approach to ask if host diversity confers protection against parasites over the range of contexts in which it has been tested.</p> <p>We synthesized the results of 102 studies, comprising 2,004 effect sizes representing a diversity of approaches and host-parasite systems. Our results validate a protective effect of genetic diversity, while revealing significant variation in its strength across biological and empirical contexts. In experimental host populations, genetic diversity reduces parasitism by ~20% for non-crop hosts and by ~50% for crop hosts. In contrast, observational studies of natural host populations show no consistent relationship between genetic diversity and parasitism, with both strong negative and positive correlations reported. This result supports the idea that, if parasites preferentially attack close relatives, the correlation of genetic diversity with parasitism could be positive or negative depending upon the potential for host populations to evolve in response to parasite selection. Taken together, these results reinforce genetic diversity as a priority for both conservation and agriculture and emphasize the challenges inherent to drawing comparisons between controlled experimental populations and dynamic natural populations.</p>
Multi-omics analysis reveals the glycolipid metabolism response mechanism in the liver of Genetically Improved Farmed Tilapia (GIFT, Oreochromis niloticus) under hypoxia stress
<p><span><b>Background: </b>Dissolved oxygen (DO) in the water is a vital abiotic factor in aquatic animal farming. A hypoxic environment affects the growth, metabolism, and immune system of fish. Glycolipid metabolism is a vital energy pathway under acute hypoxic stress, and it plays a significant role in the adaptation of fish to stressful environments. In this study, we used multi-omics integrative analyses to explore the mechanisms of hypoxia adaptation in Genetically Improved Farmed Tilapia (GIFT, <i>Oreochromis niloticus</i>). </span></p> <p><span><b>Results:</b><b> </b>The 96 h median lethal hypoxia (96h-LH50) for GIFT was determined by linear interpolation. We established control (DO: 5 mg/L) groups (CG) and hypoxic stress (96h-LH50) groups (HG) and extracted liver tissues for high-throughput transcriptome and metabolome sequencing. A total of 581 differentially expressed (DE) genes and 1250 DE metabolites were detected between CG and HG, and were annotated using tools at the KEGG database. We verified the transcript levels of eight DE genes by quantitative real-time PCR.</span></p> <p><span><b>Conclusions: </b>Analyses of essential glycolipid metabolism pathways of GIFT under hypoxia stress showed that, after 96 h of hypoxia stress, lipid metabolism became the primary metabolic pathway in GIFT. Our findings reveal the changes in metabolites and gene expression that occur under hypoxia stress, and shed light on the regulatory pathways that function under such conditions. Ultimately, this information will be useful to devise strategies to decrease the damage caused by hypoxia stress in farmed fish.</span></p>
Short-Tandem-Repeat (STR) marker set for Eurasian lynx for article: Genetic analysis indicates spatial-dependent patterns of sex-biased dispersal in Eurasian lynx in Finland
<p>Conservation and management of large carnivores requires knowledge of female and male dispersal. Such information is crucial to evaluate the population's status and thus management actions. This knowledge is challenging to obtain, often incomplete and contradictory at times. The size of the target population and the methods applied can bias the results. Also, population history and biological or environmental influences can affect dispersal on different scales within a study area. We have genotyped Eurasian lynx (180 males and 102 females, collected 2003-2017) continuously distributed in southern Finland (~23,000 km<sup>2</sup>) using 21 short tandem repeats (STR) loci and compared statistical genetic tests to infer local and sex-specific dispersal patterns within and across genetic clusters as well as geographic regions. We tested for sex-specific substructure with individual-based Bayesian assignment tests and spatial autocorrelation analyses. Differences between the sexes in genetic differentiation, relatedness, inbreeding, and diversity were analysed using population-based AMOVA, F-statistics, and assignment indices. Our results showed two different genetic clusters that were spatially structured for females but admixed for males. Similarly, spatial autocorrelation and relatedness was significantly higher in females than males. However, we found weaker sex-specific patterns for the Eurasian lynx when the data were separated in three geographical regions than when divided in the two genetic clusters. Overall, our results suggest male-biased dispersal and female philopatry for the Eurasian lynx in Southern Finland. The female genetic structuring increased from west to east within our study area. In addition, detection of male-biased dispersal was dependent on analytical methods utilized, on whether subtle underlying genetic structuring was considered or not, and the choice of population delineation. Conclusively, we suggest using multiple genetic approaches to study sex-biased dispersal in a continuously distributed species in which population delineation is difficult.</p>
Supplementary Material for Frontiers Plant Genetics and Genomics 'Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality'
<p>Authors</p> <p>Zhian N. Kamvar, Jonah C. Brooks, and Niklaus J. Grünwald</p>
Experimental and genetic analysis of selfing reveals no reinforcement in Phlox cuspidata
<p>Reinforcement is the process through which prezygotic reproductive barriers evolve in sympatry due to selection against hybridization between co-occurring, closely related species. The role of self-fertilization in reinforcement and reproductive isolation is uncertain in part because its efficiency as a barrier against heterospecific mating can depend on the timing of autonomous selfing.</p> <p>To investigate whether increased autonomous selfing has evolved as a mechanism for reinforcement, we compared <em>Phlox cuspidata</em> populations across their native Texas range using both estimates of genetic diversity and experimental manipulation with morphological measurements. Specifically, we investigated patterns of variation in floral traits and timing of selfing between individuals from allopatric populations of <em>P. cuspidata</em> and from populations sympatric with the closely related species, <em>P. drummondii</em>.</p> <p>We infer intermediate rates of selfing across field-collected individuals with no significant difference between allopatric and sympatric populations. Among greenhouse grown plants, we find no differences in timing of selfing or other floral traits including anther dehiscence timing, anther-stigma distances, autonomous selfing rate and self-seed count between allopatric and sympatric populations. However, our statistical analyses indicate that <em>P. cuspidata </em>individuals sympatric with <em>P drummondii</em> seem to have generally larger flowers compared to allopatric individuals.</p> <p>Despite strong evidence of costly hybridization with <em>P. drummondii</em>, we find no evidence of trait divergence due to reinforcement in <em>P. cuspidata. </em>Although we document nearly complete autonomous self-seed set in the greenhouse, estimates of selfing rates from genetic data imply realized selfing is much lower in nature suggesting an opportunity for reinforcing selection to act on this trait. </p>
Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry: Source and Supplementary Data
<p><em><strong>Source and Supplementary data for AANRI manuscript</strong></em></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.