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1,659 results for “structured population”
FIGURE 2 in Population Structure and Genetic Diversity in Delphinium (Ranunculaceae) Using Scot Molecular Markers
FIGURE 2: PCA plot of morphological characters revealing species delimitation in the Delphinium species; sp1= D. teheranicum; sp2= D. camptocarpum; sp3= D. lorestanicum; sp4= D. leptocarpum; sp5= D. persicum; sp 6= D. aucheri; sp7= D. anthoroideum; sp8= D. hohenackeri; sp9= D. stocksianum; sp10: D. rugulosum; sp11: D. ambiguum; sp12= D. ajacis; sp13= D. consolida; sp14= D. oliverianum; sp15= D. flavum; sp16= D. trigonelloides; sp17= D. oliganthum; sp18= D. linarioides; sp19= D. paradoxum.
FIGURE. 1 in Population Structure and Genetic Diversity in Delphinium (Ranunculaceae) Using Scot Molecular Markers
FIGURE. 1. Map of Iran shows the collection sites and provinces where Delphinium species were obtained for this study; sp1= D. teheranicum; sp2= D. camptocarpum; sp3= D. lorestanicum; sp4= D. leptocarpum; sp5= D. persicum; sp 6= D. aucheri; sp7= D. anthoroideum; sp8= D. hohenackeri; sp9= D. stocksianum; sp10: D. rugulosum; sp11: D. ambiguum; sp12= D. ajacis; sp13= D. consolida
Humid tropical vertebrates are at lower risk of extinction and population decline in forests with higher structural integrity
<p>The four Excel workbooks contain processed data in the form of humid tropical forest area under each of multiple values of the Structural Condition Index (SCI), Forest Structural Integrity Index (FSII), and Human Footprint (HFP) for Mammal, Bird, Reptile and Amphibian species. The associated README text file contains metadata to describe the data in the xlsx workbooks. Python code to replicate geospatial analyses and R code to replicate statistical analyses are provided in the respective scripts. ArcGIS Pro is required to be installed prior to running the Python script.</p>
Major biogeographic barriers in eastern Australia have shaped population structure of widely distributed Eucalyptus moluccana and its four putative subspecies
<p>We have investigated the impact of recognized biogeographic barriers on genetic differentiation of grey box (<i>Eucalyptus moluccana</i>), a common and widespread tree species of the family Myrtaceae in eastern Australian woodlands, and its previously proposed four subspecies <i>moluccana</i>, <i>pedicellata</i>, <i>queenslandica</i> and <i>crassifolia</i>.<b> </b>A range of phylogeographic analyses were conducted to examine the population genetic differentiation and subspecies genetic structure in <i>E. moluccana </i>in relation to biogeographic barriers. Slow evolving markers uncovering long term processes (chloroplast DNA) were used to generate a haplotype network and infer phylogeographic barriers. Additionally, fast evolving, hypervariable markers (microsatellites) were used to estimate demographic processes and genetic structure among five geographic regions (29 populations) across the entire distribution of <i>E. moluccana</i>. Morphological features of seedlings, such as leaf and stem traits were assessed to evaluate population clusters and test differentiation of the putative subspecies.</p> <p>Haplotype network analysis revealed twenty chloroplast haplotypes with a main haplotype in a central position shared by individuals belonging to the regions containing the four putative subspecies. Microsatellite analysis detected genetic structure between Queensland (QLD) and New South Wales (NSW) populations consistent with the McPherson Range barrier, an east-west spur of the Great Dividing Range. Substructure was detected within QLD and NSW in line with other barriers in eastern Australia. The morphological analyses supported differentiation between QLD and NSW populations, with no difference within QLD, yet some differentiation within NSW populations.</p> <p>Our molecular and morphological analyses provide evidence that several geographic barriers in eastern Australia, including the Burdekin Gap and the McPherson Range have contributed to the genetic structure of <i>E. moluccana</i>. Genetic differentiation among <i>E. moluccana </i>populations supports the recognition of some but not all the four previously proposed subspecies, with<i> crassifolia </i>being the most differentiated.</p>
Insights into Mus musculus population structure across Eurasia revealed by whole-genome analysis
<p>For more than 100 years, house mice (Mus musculus) have been used as a key animal model in biomedical research. House mice are genetically diverse, yet their genetic background at the global level has not been fully understood. Previous studies suggested that they originated in South Asia and diverged into three major subspecies almost simultaneously, approximately 350,000–500,000 years ago; however, they have spread across the world with the migration of modern humans in prehistoric and historic times (∼10,000 years ago to present), and undergone secondary contact, which have complicated the genetic landscape of wild house mice. In this study, we sequenced the whole genomes of 98 wild house mice collected from Eurasia, particularly East Asia, Southeast Asia, and South Asia. We found that although wild house mice consist of three major genetic groups corresponding to the three major subspecies, individuals representing admixture between subspecies are much more ubiquitous than previously recognized. Furthermore, several samples showed an incongruent pattern of genealogies between mitochondrial and autosomal genomes. Using samples likely retaining the original genetic components of subspecies with least admixture, we estimated the pattern and timing of divergence among the subspecies. The results are important for understanding the genetic diversity of wild mice on a global level and the information will be particularly useful in future biomedical and evolutionary studies using laboratory mice established from these wild mice.</p>
Fig. 4 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 4. Parameter estimates for fixed effects (β) in spatial mixed effects models (spaMM) for each species, with 95% CIs, testing the effects of Elevation (scaled), AMT (scaled), and Elevation * AMT interaction on traits; Asterisk indicates the CIs did not encompass zero. If no estimate is shown that variable was not included in the model for that species. Maps show spatial trends of trait value from interpolation of estimates for each model (filled.mapMM function in spaMM). Note, for B. vosnesenskii mass and pw-Empty, the low-AIC models were intercept plus random effect only, but for visualization, results are presented for the next best model with at least one fixed effect (seeTable 2 for model details).
Fig. 3 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 3. Effect predictions (with 95% CI) of mass (field and empty), thorax size (ITS), forewing area, and transformed wing loading (pw-Field, pw-Empty) against (A) latitude, (B) AMT (Worldclim BIO1 variable), and (C) elevation from univariate linear mixed effects models for B. vancouverensis (blue) and B. vosnesenskii (red). Statistical analyses were conducted on log-transformed mass, ITS, and wing loading (see SuppTable S4 [online only]), but responses were back-transformed to the original scale for plotting (plot_model function in sjPlot). Lines are labeled with significance estimate of the β parameter estimated from lmerTest (*P <0.05; ***P <0.001; unlabeled = not significant, CI encompasses zero).
Fig. 1 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 1. Map of sampling localities in California, Oregon, and Washington, United States.Bombus vancouverensis is indicated by circles,B. vosnesenskii by triangles, and additional B. vosnesenskii from 2013 used to improve elevational coverage at middle latitudes for some traits by open triangles. Grayscale shading reflects a digital elevation model for the region.
Fig. 5 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 5. Relationships among space, population structure (FST), and average mass and wing loading (pw) differences among pair of populations for (A) B. vancouverensis and (B) B. vosnesenskii. Panels include plots of isolation by distance (FST by geographic distance), effects of population structure on mass, and the effects of elevation on mass and pw residuals from models including FST and geographic distance.The latter panels are included to illustrate the remaining positive effect of elevational separation on wing loading differences among B. vancouverensis populations after accounting for space and population structure, but not for B. vosnesenskii populations and not for mass in either species (seeTable 3 and Supp Fig. S6 [online only]).
Fig. 2 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane
Fig. 2. Boxplots (shown for site means) and tests of differences between species in overall field mass (A), empty mass (B), ITS (C), forewing area (D), pw-Field (E), and pw-Empty (F). Statistical tests are summaries taken from linear mixed models (full report and parameter estimates in Supp Table S1 [online only]), showing marginal (R 2) and conditional (R 2) R2 values and with df for the species effect t statistic and P-values (***P <0.001; N.S. = not significant) associated with the M C relevant fixed effect estimated using lmertest. Mass, ITS, and pw values were log-transformed for statistical tests but plotted untransformed. Panels G–L show scatterplots of correlations among several traits for each bee and are presented with Pearson's correlation coefficients (r) and 95% CIs (see SuppTables 2 and 3 [online only] and Supp Figs. S2–S4 [online only] for additional trait correlation statistical details).
Supplementary material 3 from: Astuti G, Roma-Marzio F, D'Antraccoli M, Bedini G, Carta A, Sebastiani F, Bruschi P, Peruzzi L (2017) Conservation biology of the last Italian population of Cistus laurifolius (Cistaceae): demographic structure, reproductive success and population genetics. Nature Conservation 22: 169-190. https://doi.org/10.3897/natureconservation.22.19809
Supplementary material 3 from: Astuti G, Roma-Marzio F, D'Antraccoli M, Bedini G, Carta A, Sebastiani F, Bruschi P, Peruzzi L (2017) Conservation biology of the last Italian population of Cistus laurifolius (Cistaceae): demographic structure, reproductive success and population genetics. Nature Conservation 22: 169-190. https://doi.org/10.3897/natureconservation.22.19809
Supplementary material 2 from: Astuti G, Roma-Marzio F, D'Antraccoli M, Bedini G, Carta A, Sebastiani F, Bruschi P, Peruzzi L (2017) Conservation biology of the last Italian population of Cistus laurifolius (Cistaceae): demographic structure, reproductive success and population genetics. Nature Conservation 22: 169-190. https://doi.org/10.3897/natureconservation.22.19809
Supplementary material 2 from: Astuti G, Roma-Marzio F, D'Antraccoli M, Bedini G, Carta A, Sebastiani F, Bruschi P, Peruzzi L (2017) Conservation biology of the last Italian population of Cistus laurifolius (Cistaceae): demographic structure, reproductive success and population genetics. Nature Conservation 22: 169-190. https://doi.org/10.3897/natureconservation.22.19809
Supplementary material 1 from: Astuti G, Roma-Marzio F, D'Antraccoli M, Bedini G, Carta A, Sebastiani F, Bruschi P, Peruzzi L (2017) Conservation biology of the last Italian population of Cistus laurifolius (Cistaceae): demographic structure, reproductive success and population genetics. Nature Conservation 22: 169-190. https://doi.org/10.3897/natureconservation.22.19809
Supplementary material 1 from: Astuti G, Roma-Marzio F, D'Antraccoli M, Bedini G, Carta A, Sebastiani F, Bruschi P, Peruzzi L (2017) Conservation biology of the last Italian population of Cistus laurifolius (Cistaceae): demographic structure, reproductive success and population genetics. Nature Conservation 22: 169-190. https://doi.org/10.3897/natureconservation.22.19809
Strong genetic structure and divergence of marginal populations of black poplar in Poland
<p><strong>The dataset comprises nuclear microsatellite data (PCR products lengths) used in the paper "Strong genetic structure and divergence of marginal populations of black poplar in Poland".</strong></p> <p>Abstract: Genetic diversity is crucial to secure the survival and sustainability of ecosystems. Given anthropogenic pressure, as well as the projected alterations connected with the level and circulation of water, riparian forests are of particular concern. In this paper, we assessed the genetic variation of black poplar – one of the keystone tree species of riverine forests. The natural habitats of black poplar have been severely transformed leading to a significant decline of its population size. Using a set of 18 nuclear microsatellites and geographic location data, we studied 26 remnant populations (1,261 trees) located along the biggest river valleys in Poland. Our main goal was to assess the overall genetic variation and to verify if range fragmentation and habitat transformation have disrupted gene exchange among populations. Genotyping revealed that 261 trees were clones. The level of clonality was generally higher in the two most transformed river valleys (the Oder and Warta). All populations have probably gone through a drastic genetic bottleneck in the distant past, and most of them have low effective population sizes. Still, the overall level of genetic variation remains high, but certain populations require attention due to their lower genetic variation, higher clonality and strong spatial genetic structure. Genetic differentiation was low, yet Bayesian clustering supported the existence of 11 separate gene pools. According to the results, the intensity of gene exchange is very low and limited to adjacent stands. Relatively free gene flow occurs only along the Vistula, particularly in its middle section which is characterized by the highest genetic variation. The greatest genetic structuring was observed along the Oder. Populations located at the range margin had unique gene pools and showed signs of genetic divergence and reduction of variation caused by genetic drift. We conclude that human activities have seriously impacted the gene pool of black poplar in Poland by disrupting landscape connectivity and preventing the species from generative reproduction. The study provides practical guidelines on how to develop and implement the conservation program for the gene pool of black poplar in Poland.</p>
Data from "Population genomic structure of Lemna minor and the cryptic species L. japonica in Switzerland"
<p>SNP data and sample annotation:</p> <ul> <li>sampleTab.csv contains the sample annotation (species and population)</li> <li>L.minor.reference.bcftools.snps.vcf.gz(.tbi) contains SNPs from all samples using the L. minor reference genome (Lm7210)</li> <li>L.japonica.reference.bcftools.snps.vcf.gz(.tbi) contains SNPs from all samples using the L. japonica reference genome (Lj9421)</li> </ul>
Data for: Population structure and inbreeding in wild house mice (Mus musculus) at different geographic scales
<p>House mice (<em>Mus musculus</em>) have spread globally as a result of their commensal relationship with humans. In the form of laboratory strains, both inbred and outbred, they are also among the most widely-used model organisms in biomedical research. Although the general outlines of house mouse dispersal and population structure are well known, details have been obscured by either limited sample size or small numbers of markers. Here we examine ancestry, population structure, and inbreeding using SNP microarray genotypes in a cohort of 814 wild mice spanning five continents and all major subspecies of <em>Mus</em>, with a focus on <em>M. m. domesticus</em>. We find that the major axis of genetic variation in <em>M. m. domesticus</em> is a south-to-north gradient within Europe and the Mediterranean. The dominant ancestry component in North America, Australia, New Zealand, and various small offshore islands is of northern European origin. Next, we show that inbreeding is surprisingly pervasive and highly variable, even between nearby populations. By inspecting the length distribution of homozygous segments in individual genomes, we find that inbreeding in commensal populations is mostly due to consanguinity. Our results offer new insight into the natural history of an important model organism for medicine and evolutionary biology.</p>
Double Trouble : Multiple infections and the coevolution of virulence-resistance in structured host-parasite populations - Scripts, Data and Supplementary Material
<p>Supplementary material</p> <p> </p> <p>Contains the Mathematica notebook for analytical and numerical computations, and figure generation.</p> <p>An Rscript used to reproduce the coevolutionary figures from section "Coevolution"</p> <p>The set of appendices in a .pdf file.</p>
The population genetics of structural variants in grapevine domestication
<p><strong>The genome assembly: </strong><a href="https://zenodo.org/api/files/988c0749-aec9-42fe-865e-b09b140e2068/Chardonnay.fa.fasta?versionId=86a512b8-12a6-4f4d-ac5d-acc26d74589f">Chardonnay.fa.fasta</a> </p> <p><strong>The gene annotation: </strong><a href="https://zenodo.org/api/files/988c0749-aec9-42fe-865e-b09b140e2068/Chardonnay.annotation_sorted.gff.gz?versionId=2e5878bc-cf53-489b-ac71-2602f9ba4d2e">Chardonnay.annotation_sorted.gff.gz</a></p> <p><strong>The TE annotation: </strong><a href="https://zenodo.org/api/files/988c0749-aec9-42fe-865e-b09b140e2068/Chardonnay.annotation_te_sorted.gff3.gz?versionId=95780497-e0e7-4a7b-8860-74072d7f7bb2">Chardonnay.annotation_te_sorted.gff3.gz</a></p>
Fig. 4 in Genetic structure of Parnassius mnemosyne (Lepidoptera: Papilionidae) populations in the Carpathian Basin
Fig. 4 Results of Bayesian clustering analyses in P. mnemosyne. The bar plots of all individuals assuming K = 2 and K = 3. NM North Hungarian Mountains, TM Transdanubian Mountains, KÖR Körös region, BAEC Bereg–Apuseni–East Carpathian region
Fig. 5 in Species status and population structure of mussels (Mollusca: Bivalvia: Mytilus spp.) in the Wadden Sea of Lower Saxony (Germany)
Fig. 5 Phylogenetic tree of the concatenated COI and VD1 * haplotypes (n 084) based on maximum likelihood estimates as constructed using RAxML. Asterisks indicate bootstrap values ≥95%
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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.