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1,467 results for “Genetic structure”
Figure 5 from: Muhammad F, Lü Z-m, Liu L, Gong L, Du X, Shafi M, Kaleri HA (2018) Genetic structure of Octopus minor around Chinese waters as indicated by nuclear DNA variations (Mollusca, Cephalopoda). ZooKeys 775: 1-14. https://doi.org/10.3897/zookeys.775.24258
Figure 5 Median-joining networking drawn based on ODH gene haplotypes. Colours represent the corresponding population frequencies. Key: Dalian; Dongshan; Nantong; Qingdao; Shanghai; Wenzhou; Xiamen; Zhoushan.
Figure 2 from: Muhammad F, Lü Z-m, Liu L, Gong L, Du X, Shafi M, Kaleri HA (2018) Genetic structure of Octopus minor around Chinese waters as indicated by nuclear DNA variations (Mollusca, Cephalopoda). ZooKeys 775: 1-14. https://doi.org/10.3897/zookeys.775.24258
Figure 2 Neighbour-joining phylogenetic tree constructed based on RD gene sequences. Key: DL = Dalian, N = Nantong, Q = Qingdao, S = Shanghai, W = Wenzhou, X = Xiamen, Z = Zhoushan.
Figure 4 from: Muhammad F, Lü Z-m, Liu L, Gong L, Du X, Shafi M, Kaleri HA (2018) Genetic structure of Octopus minor around Chinese waters as indicated by nuclear DNA variations (Mollusca, Cephalopoda). ZooKeys 775: 1-14. https://doi.org/10.3897/zookeys.775.24258
Figure 4 Median-joining networking drawn based on RD gene haplotypes. Colours represent the corresponding population frequencies. Key: Dalian; Dongshan; Nantong; Qingdao; Shanghai; Wenzhou; Xiamen; Zhoushan.
Figure 3 from: Muhammad F, Lü Z-m, Liu L, Gong L, Du X, Shafi M, Kaleri HA (2018) Genetic structure of Octopus minor around Chinese waters as indicated by nuclear DNA variations (Mollusca, Cephalopoda). ZooKeys 775: 1-14. https://doi.org/10.3897/zookeys.775.24258
Figure 3 Neighbour-joining tree constructed based on the ODH gene. Key: DL = Dalian, N = Nantong, Q = Qingdao, S = Shanghai, W = Wenzhou, X = Xiamen, Z = Zhoushan.
Figure 6 from: Liu L, Zhang X, Li C, Zhang H, Yanagimoto T, Song N, Gao T (2019) Population genetic structure of Marbled Rockfish, Sebastiscus marmoratus (Cuvier, 1829), in the northwestern Pacific Ocean. ZooKeys 830: 127-144. https://doi.org/10.3897/zookeys.830.30586
Figure 6 Bayesian skyline plot showing the effective female S.marmoratus population size through time. Black solid lines are median estimates of NeT (Ne=effective female population size; T=generation time); blue shading represents the 95% confidence interval of NeT. The y-axis was plotted on a logarithmic scale.
Figure 2 from: Liu L, Zhang X, Li C, Zhang H, Yanagimoto T, Song N, Gao T (2019) Population genetic structure of Marbled Rockfish, Sebastiscus marmoratus (Cuvier, 1829), in the northwestern Pacific Ocean. ZooKeys 830: 127-144. https://doi.org/10.3897/zookeys.830.30586
Figure 2 Phylogenetic tree of control region haplotypes constructed using neighbor-joining algorithms of S.marmoratus with S.schlegelii as outgroup.
Figure 4 from: Liu L, Zhang X, Li C, Zhang H, Yanagimoto T, Song N, Gao T (2019) Population genetic structure of Marbled Rockfish, Sebastiscus marmoratus (Cuvier, 1829), in the northwestern Pacific Ocean. ZooKeys 830: 127-144. https://doi.org/10.3897/zookeys.830.30586
Figure 4 The observed pairwise difference (bars) and the expected mismatch distributions under the sudden-expansion model (solid line) of mtDNA control region haplotypes in S.marmoratus.
Supporting code and data for: Exploring the role of asexual multiplication in poplar rust epidemics: impact on diversity and genetic structure
<p>This is the first release of the updated code for the analyses of the related article published in Molecular Ecology.</p>
High genetic diversity but no geographic structure of Aedes albopictus populations in Reunion Island _ Dataset
<p>Microsatellite dataset of <em>Aedes albopictus</em> individuals sampled in Reunion Island. </p>
Figure 3. a in Mitochondrial genetic diversity and structuring of northern white-breasted hedgehogs from the Central Balkans
Figure 3. a) Median-joining network of the mtDNA control region haplotypes of E. roumanicus and E. concolor. Circle sizes are proportional to haplotype frequencies, while circle colors correspond to defined regions as shown in the legend. Each branch represents one mutational step; if more than one mutation step is present, it is denoted by the numbers. The MJ network is presented as the shortest tree, while lost connections between haplotypes after MP processing are shown with dashed lines. Black circles represent median vectors (unsampled or ancestral haplotypes). b) Bayesian phylogenetic tree showing relationships among 30 haplotypes of E. roumanicus and E. concolor. The trees were rooted using E. europaeus as an out-group. Haplotype names correspond to those given in Table 1 and Table S1.
Data for "Proteome-wide prediction of mode of inheritance and molecular mechanism underlying genetic diseases using structural interactomics"
Open the record for dataset details and reuse information.
Landscape population genetics structure in the West Nile virus vector, Culex tarsalis
<p>RADseq raw data</p>
Data from: Inferring the origin of populations introduced from a genetically structured native range by approximate Bayesian computation: case study of the invasive ladybird Harmonia axyridis
Correct identification of the source population of an invasive species is a prerequisite for testing hypotheses concerning the factors responsible for biological invasions. The native area of invasive species may be large, poorly known and/or genetically structured. Because the actual source population may not have been sampled, studies based on molecular markers may generate incorrect conclusions about the origin of introduced populations. In this study, we characterized the genetic structure of the invasive ladybird Harmonia axyridis in its native area using various population genetic statistics and methods. We found that H. axyridis native area most likely consisted of two geographically distinct genetic clusters located in eastern and western Asia. We then performed approximate Bayesian computation (ABC) analyses on controlled simulated microsatellite data sets to evaluate: (i) the risk of selecting incorrect introduction scenarios, including admixture between sources, when the populations of the native area are genetically structured and sampling is incomplete, (ii) the ability of ABC analysis to minimize such risks by explicitly including unsampled populations in the scenarios compared. Finally, we performed additional ABC analyses on real microsatellite data sets to retrace the origin of biocontrol and invasive populations of H. axyridis, taking into account the possibility that the structured native area may have been incompletely sampled. We found that the invasive population in eastern North America, which has served as the bridgehead for worldwide invasion by H. axyridis, was probably formed by an admixture between the eastern and western native clusters. This admixture may have facilitated adaptation of the bridgehead population.
Data from: Genetic variation and structure of Diaphorina citri (Hemiptera:Liviidae) in populations from México
The Asian citrus psyllid, Diaphorina citri Kuwayama, is native to Asia but has recently invaded North America. Asian citrus psyllid is a significant pest of citrus crops by its direct feeding but, more importantly, as the vector of the bacterium 'Candidatus Liberibacter asiaticus', which causes Huanglongbing disease. Asian citrus psyllid was first found in México in 2001 and 2002 and, since then, has spread quickly across the country, suggesting rapid adaptation to new environments. Yet, we lack information on the genetic variation and structure that could facilitate or inhibit adaptation. Using six microsatellite markers, we analyzed genetic variation and structure among six localities in México: three in western states near the Pacific coast and two in the Yucatán Peninsula near the Gulf of México. We found low genetic diversity (no more than three alleles per locus) and intermediate differentiation between all populations. Asian citrus psyllid populations clustered into two genetic groups, but, surprisingly, these clusters were present in western populations. The first group included El Arenal, and the second group included Autlán de Navarro, Colima, and Tecomán. Interestingly, both of the Yucatán populations shared variation from the two clusters, suggesting admixture. We infer that reproductive isolation, barriers to gene flow, local selection, and the possibility of multiple invasions have influenced the current genetic structure of Asian citrus psyllid in México.
Data from: Environmental conditions affect spatial genetic structures and dispersal patterns in a solitary rodent
The study of the spatial distribution of relatives in a population under contrasted environmental conditions provides critical insights into the flexibility of dispersal behaviour and the role of environmental conditions in shaping population relatedness and social structure. Yet few studies have evaluated the effects of fluctuating environmental conditions on relatedness structure of solitary species in the wild. The aim of this study was to determine the impact of interannual variations in environmental conditions on the spatial distribution of relatives [spatial genetic structure (SGS)] and dispersal patterns of a wild population of eastern chipmunks (Tamias striatus), a solitary rodent of North America. Eastern chipmunks depend on the seed of masting trees for reproduction and survival. Here, we combined the analysis of the SGS of adults with direct estimates of juvenile dispersal distance during six contrasted years with different dispersal seasons, population sizes and seed production. We found that environmental conditions influences the dispersal distances of juveniles and that male juveniles dispersed farther than females. The extent of the SGS of adult females varied between years and matched the variation in environmental conditions. In contrast, the SGS of males did not vary between years. We also found a difference in SGS between males and females that was consistent with male-biased dispersal. This study suggests that both the dispersal behaviour and the relatedness structure in a population of a solitary species can be relatively labile and change according to environmental conditions.
Data from: Temporal genetic structure in a poecilogonous polychaete: the interplay of developmental mode and environmental stochasticity
Background: Temporal variation in the genetic structure of populations can be caused by multiple factors, including natural selection, stochastic environmental variation, migration, or genetic drift. In benthic marine species, the developmental mode of larvae may indicate a possibility for temporal genetic variation: species with dispersive planktonic larvae are expected to be more likely to show temporal genetic variation than species with benthic or brooded non-dispersive larvae, due to differences in larval mortality and dispersal ability. We examined temporal genetic structure in populations of Pygospio elegans, a poecilogonous polychaete with within-species variation in developmental mode. P. elegans produces either planktonic, benthic, or intermediate larvae, varying both among and within populations, providing a within-species test of the generality of a relationship between temporal genetic variation and larval developmental mode. Results: In contrast to our expectations, our microsatellite analyses of P. elegans revealed temporal genetic stability in the UK population with planktonic larvae, whereas there was variation indicative of drift in temporal samples of the populations from the Baltic Sea, which have predominantly benthic and intermediate larvae. We also detected temporal variation in relatedness within these populations. A large temporal shift in genetic structure was detected in a population from the Netherlands, having multiple developmental modes. This shift could have been caused by local extiction due to extreme environmental conditions and (re)colonization by planktonic larvae from neighboring populations. Conclusions: In our study of P. elegans, temporal genetic variation appears to be due to not only larval developmental mode, but also the stochastic environment of adults. Large temporal genetic shifts may be more likely in marine intertidal habitats (e.g. North Sea and Wadden Sea) which are more prone to environmental stochasticity than the sub-tidal Baltic habitats. Sub-tidal and/or brackish (less saline) habitats may support smaller P. elegans populations and these may be more susceptible to the effects of random genetic drift. Moreover, higher frequencies of asexual reproduction and the benthic larval developmental mode in these populations leads to higher relatedness and contributes to drift. Our results indicate that a general relationship between larval developmental mode and temporal genetic variation may not exist.
Data From: Genetic structure of recently fragmented suburban populations of European stag beetle
<p>Habitat loss and fragmentation due to urbanisation can negatively affect metapopulation persistence when gene flow among populations is reduced and population sizes decrease. Inference of patterns and processes of population connectivity derived from spatial genetic analysis has proven invaluable for conservation and management. However, a more complete account of population dynamics may be obtained by combining spatial and temporal sampling. We, therefore, performed a genetic study on European stag beetle (<i>Lucanus cervus</i> L.) populations in a suburban context using samples collected in three locations and during the period 2002-2016. The sampling area has seen recent landscape changes which resulted in population declines. Through the use of a suite of FST, clustering analysis, individual assignment, and relatedness analysis we assessed fine scale spatiotemporal genetic variation within and among habitat patches using 283 individuals successfully genotyped at 17 microsatellites. Our findings suggested the three locations to hold demographically independent populations, at least over time scales of relevance to conservation, though with higher levels of gene flow in the past. Contrary to expectation from tagging studies, dispersal appeared to be mainly female-biased. Although the life cycle of stag beetle suggests its generations to be discrete, no clear temporal structure was identified, which could be attributed to the varying duration of larval development. Since population bottlenecks were detected and estimates of effective number of breeders were low, conservation actions are eminent which should include the establishment of suitable dead wood for oviposition on both local and regional scales to increase (re)colonisation success and connectivity among current populations.</p>
Data from: Fine-scale spatial genetic structure across the species range reflects recent colonization of high elevation habitats in silver fir (Abies alba Mill.)
<p class="western"><span>Variation in genetic diversity across species ranges has long been recognized as highly informative for assessing populations' resilience and adaptive potential. The spatial distribution of genetic diversity within populations, referred to as fine-scale spatial genetic structure (FSGS), also carries information about recent demographic changes, yet it has rarely been connected to range scale processes. We studied eight silver fir (<i>Abies alba </i>Mill.<i>)</i> population pairs (sites), growing at high and low elevations, representative of the main genetic lineages of the species. A total of 1368 adult trees and 540 seedlings were genotyped using 137 and 116 single nucleotide polymorphisms (SNPs), respectively. Sites revealed a clear east-west isolation-by-distance pattern consistent with the post-glacial colonization history of the species. Genetic differentiation among sites (<i>F</i><sub>CT</sub>=0.148) was an order of magnitude greater than between elevations within sites (<i>F</i><sub>SC</sub>=0.031), nevertheless high elevation populations consistently exhibited a stronger FSGS. Structural equation modeling revealed that elevation and, to a lesser extent, post-glacial colonization history, but not climatic and habitat variables, were the best predictors of FSGS across populations. These results suggest that high elevation habitats have been colonized more recently across the species range. Additionally, paternity analysis revealed a high reproductive skew among adults and a stronger FSGS in seedlings than in adults, suggesting that FSGS may conserve the signature of demographic changes for several generations. Our results emphasize that spatial patterns of genetic diversity within populations provide information about demographic history complementary to non-spatial statistics, and could be used for genetic diversity monitoring, especially in forest trees.</span></p>
Data from: How obstacles perturb population fronts and alter their genetic structure
As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle's shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call 'geometry-enhanced genetic drift', complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles.
Figure 2 in Complete mitogenome of Chinese shrew mole Uropsilus soricipes (Milne- Edwards, 1871) (Mammalia: Talpidae) and genetic structure of the species in the Jiajin Mountains (China)
Figure 2. Gene content and organization of mitochondrial genome of Uropsilus soricipes.
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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.