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15,022 results for “differentiation”
Data from: Drift happens: molecular genetic diversity and differentiation among populations of jewelweed (Impatiens capensis Meerb.) reflect fragmentation of floodplain forests
Landscape features often shape patterns of gene flow and genetic differentiation in plant species. Populations that are small and isolated enough also become subject to genetic drift. We examined patterns of gene flow and differentiation among 12 floodplain populations of the selfing annual jewelweed (Impatiens capensis Meerb.) nested within four river systems and two major watersheds in Wisconsin, USA. Floodplain forests and marshes provide a model system for assessing the effects of habitat fragmentation within agricultural/urban landscapes and for testing whether rivers act to genetically connect dispersed populations. We generated a panel of 12,856 single nucleotide polymorphisms and assessed genetic diversity, differentiation, gene flow, and drift. Clustering methods revealed strong population genetic structure with limited admixture and highly differentiated populations (mean multilocus FST = 0.32, FST' = 0.33). No signals of isolation by geographic distance or environment emerged, but alleles may flow along rivers given that genetic differentiation increased with river distance. Differentiation also increased in populations with fewer private alleles (R2 = 0.51) and higher local inbreeding (R2 = 0.22). Populations varied greatly in levels of local inbreeding (FIS = 0.2 to 0.9) and FIS declined in smaller, more isolated populations. These results suggest that genetic drift dominates other forces in structuring these Impatiens populations. In rapidly changing environments, species must migrate or genetically adapt. Habitat fragmentation limits both processes, potentially compromising the ability of species to persist in fragmented landscapes.
Data from: Discordant patterns of genetic and phenotypic differentiation in five grasshopper species co-distributed across a microreserve network
<p>Conservation plans can be greatly improved when information on the evolutionary and demographic consequences of habitat fragmentation is available for several co-distributed species. Here, we study spatial patterns of phenotypic and genetic variation among five grasshopper species that are co-distributed across a network of microreserves but show remarkable differences in dispersal-related morphology (body size and wing length), degree of habitat specialization and extent of fragmentation of their respective habitats in the study region. In particular, we tested the hypothesis that species with preferences for highly fragmented microhabitats show stronger genetic and phenotypic structure than co-distributed generalist taxa inhabiting a continuous matrix of suitable habitat. We also hypothesized a higher resemblance of spatial patterns of genetic and phenotypic variability among species that have experienced a higher degree of habitat fragmentation due to their more similar responses to the parallel large-scale destruction of their natural habitats. In partial agreement with our first hypothesis, we found that genetic structure, but not phenotypic differentiation, was higher in species linked to highly fragmented habitats. We did not find support for congruent patterns of phenotypic and genetic variability among any studied species, indicating that they show idiosyncratic evolutionary trajectories and distinctive demographic responses to habitat fragmentation across a common landscape. This suggests that conservation practices in networks of protected areas require detailed ecological and evolutionary information on target species in order to focus management efforts on those taxa that are more sensitive to the effects of habitat fragmentation.</p>
Data from: Differential gene expression in relation to mating system in Peromyscine rodents
Behaviors that increase an individual's exposure to pathogens are expected to have important effects on immunoactivity. Because sexual reproduction typically requires close contact among conspecifics, mating systems provide an ideal opportunity to study the immunogenetic correlates of behaviors with high versus low risks of pathogen exposure. Despite logical links between polygynandrous mating behavior, increased pathogen exposure, and greater immunoactivity, these relationships have seldom been examined in nonhuman vertebrates. To explore interactions among these variables in a different lineage of mammals, we used RNAseq to study the gene expression profiles of liver tissue—a highly immunoactive organ—from sympatric populations of the monogamous California mouse (Peromyscus californicus) and two polygynandrous congeners (P. maniculatus and P. boylii). Differential expression and co‐expression analyses revealed distinct patterns of gene activity among species, with much of this variation associated with differences in mating system. This tendency was particularly pronounced for MHC genes, with multiple MHC Class I genes being upregulated in the two polygynandrous species, as expected if exposure to sexually transmitted pathogens varies with mating system. Our results underscore the role of mating behavior in influencing patterns of gene expression and highlight the use of emerging transcriptomic tools in behavioral studies of free‐living animals.
Data from "Corset: enabling differential gene expression analysis for de novo assembled transcriptomes"
<p>This dataset contains de novo transcriptome assemblies for three publicly available RNA-seq dataset (SRA055442, SRR453566-SRR453571 and GSE37704 ). For each assembly we also provide a table with the read counts per contig, the output from corset (clusters and counts), and the results from a genome-based analysis. This dataset was used to assess the performance of the corset software. More detail is provided in the paper: Nadia M Davidson and Alicia Oshlack,<strong> </strong>Corset: enabling differential gene expression analysis for de novo assembled transcriptomes, <em>Genome Biology</em> 2014, <strong>15</strong>:410. http://genomebiology.com/2014/15/7/410/abstract</p>
February 2017 Western Turkey Earthquake Swarm Sentinel-1 TOPS Differential Interferogram (20170131-20170212)
<p>In february 2017 a series of earthquakes affected the Biga Peninsula in Western Turkey. Over 350 buildings sustained extensive damage. The seismic events occurred at the intersection of the Kestanbol Fault and the Edremit Fault Zone. The Sentinel-1 TOPS co-seismic interferogram was generated with the ESA SNAP toolbox (http://step.esa.int/).</p> <p>S1A data were downloaded from the Sentinel-1 Scientific Data Hub: S1A_20170131-S1A_20170212 from ASCENDING orbit 131.</p> <p> </p>
Mountain landscape connectivity and subspecies appurtenance shape genetic differentiation in natural plant populations of the snapdragon (Antirrhinum majus L.)
<p>This dataset provides the raw data for the population genetic analyses for the article: "Mountain landscape connectivity and subspecies appurtenance shape genetic differentiation in natural plant populations of the snapdragon (Antirrhinum majus L.)" by Benoit Pujol; Juliette Archambeau; Aurore Bontemps; Mylène Lascoste; Sara Marin; and Alexandre Meunier found in the journal "Botany Letters", Vol 164 pp. 111-119 (DOI: 10.1080/23818107.2017.1310056).</p> <p>Link to journal open access article: http://www.tandfonline.com/doi/pdf/10.1080/23818107.2017.1310056</p> <p>Link to Zenodo article reporsitory: https://zenodo.org/record/801169</p> <p>The datafile includes three data sheets:</p> <p>Data, which contains for each plant : the name of the population, the name of the sampled individual, the subspecies, the latitude of the population, the longitude of the population, the altitudinal elevation of the population in meters, and the microsatellite genotype of each plant. Genotype data is recorded by locus (two columns for the two alleles at one locus). Locus name is found as the title of the column. The record for each allele is its allele size.</p> <p>valleys 1 and valleys 2, which contains the association between populations and valleys following the two scenarios that we analyzed in the paper.</p> <p>Microsatelite loci were developed during previous work: see the following paper for more details: Debout, G., E. Lhuillier, P.-J. Malé, B. Pujol, and C. Thébaud. 2012. Development and characterization of 24 polymorphic microsatellite loci in two Antirrhinum majus subspecies (Plantaginaceae) using pyrosequencing technology. Conservation Genetics Resources 4:75-79.</p>
Differential gene expression in iPSC-derived macrophages after IFNg stimulation and Salmonella infection
<p>We used likelihood ratio test implemented in DESeq2 v1.10.0 (test = “LRT”) to test if a model that allowed different mean expression in each condition explained the data better than a null model assuming the same mean expression across conditions. See the manuscript for more details: http://www.biorxiv.org/content/early/2017/05/18/102392 .</p> <p>We used the following commands in DESeq2:<br> #Run DESeq2<br> dds = DESeq2::DESeqDataSetFromMatrix(combined_expression_data_filtered$counts, design, ~condition_name) <br> dds = DESeq2::DESeq(dds, test = "LRT", reduced = ~ 1)</p> <p>#Extract differentially expressed genes in each condition<br> ifng_genes = results(dds, contrast=c("condition_name","IFNg","naive")) <br> sl1344_genes = results(dds, contrast=c("condition_name","SL1344","naive")) <br> ifng_sl1344_genes = results(dds, contrast=c("condition_name","IFNg_SL1344","naive"))</p>
Single-cell RNA sequencing identifies shared differentiation paths of mouse thymic innate T cells
<p>scRNA sequencing datasets used in the paper titled 'Single-cell RNA sequencing identifies shared differentiation paths of mouse thymic innate T cells' published in Nature Communications<br> <br> https://www.nature.com/articles/s41467-020-18155-8</p>
Grazing halos reveal differential ecosystem vulnerabilities in vegetated habitats
<p>Minguito-Frutos_etal_2024.xlsx contains the data to explore the relationship between habitat productivity and sea urchin consumption under different contexts. This relationship is represented by individually-produced sea urchin grazing halos, which are influenced by biotic and abiotic factors. </p> <p>Minguito-Frutos_etal_2024.R contains the R reproducible code to run all the analyses carried out in this study. </p> <p>--------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>Minguito-Frutos_etal_2025.R</strong> contains the code used in the final version of the manuscript accepted for publication in <em>Ecology</em>. This script includes the final specifications of the linear mixed models (LMMs) fitted in the study, along with all statistical evaluations and the corresponding visualizations.</p>
Negative Differential Resistance, Instability, and Critical Transition in Lightning Leader
<p>There is a challenging issue of die out and restrike of leaders in a burst of lightning event, such as multiplicity of strokes in grounded flash or recoil leader in cloud flash, although the argument involves the effects of channel characteristic of negative differential resistance instability, there is internal consistency about the instability, the bi-stability of insulation and induction and their critical transition from the view of bifurcation theory of nonlinear dynamics. In this paper, we examined the differential resistance characteristics of the leader-streams lighting system, we associate the leader-streamer channel differential resistance characteristics and sign change with channel state and instability transitions. The critical current and potential difference conditions for the stable transition of the leader-streamer channel are investigated. It is found that the necessary current required for the stable development of the channel is increased with the length of the leader channel, while the internal channel electric field of the leader decreases accordingly.</p>
Dataset for comparison of QuantumPower method to the differential PJVS method.
<p>Dataset for comparison of QuantumPower method to the differential PJVS method.</p> <p> </p> <p>Two methods for calibration of low frequency AC voltage using quantum voltage standard were compared: 1, classic differential method where digitizer measures difference between device under test and a step sine like signal generated by programmable josephson voltage standard. 2, quantum power method, where digitiser is first calibrated using programmable josephson voltage standard, and after a switch of multiplexer digitiser directly measures voltage of a device under test.</p> <p> </p> <p>To obtain the data, QPSW software was used:</p> <p>https://github.com/KaeroDot/QPsw</p> <p> </p> <p>Author: Martin Šíra</p> <p> </p> <p>Contact: Czech Metrology Institute, Okružní 31, 638 00 Brno, msira@cmi.cz</p> <p> </p> <p>Part of project Quantum traceability for AC power standards, QuantumPower, Project Number: 19RPT01. This project (19RPT01) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.</p> <p> </p> <p>https://www.euramet.org/research-innovation/search-research-projects/details/project/quantum-traceability-for-ac-power-standards/</p>
Figure 8 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 8. Daphnia tanakai sp. nov., male from Lake Midori-ga-ike, Japan. A, lateral view. B, caudal spine. C, head. D, E, armature of antero-ventral and posterior portion of valve. F, G, postabdomen and postabdominal claw. H, male antenna I. I, tip of male seta ('flagellum') on antenna I. J, K, limb I and its distal portion. L–O, distal-most endite of limb II.
Figure 7 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 7. Daphnia tanakai sp. nov., thoracic limbs of parthenogenetic female from Lake Midori-ga-ike, Japan. A, B, limb I. C, D, anterior seta on its endite 3 and 2. E, limb II. F, G, stiff seta on its inner-distal end. H, gnathobase II. I, J, limb III and its inner-distal portion. K, L, limb IV and its inner-distal portion. M, N, limb V and distal portion of its exopodite.
Figure 6 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 6. Daphnia tanakai sp. nov. from Lake Midori-ga-ike, collected on August 30, 2004 by S. Tanaka (A–F, K–O) and Lake Kagami-ike, collected on September 01, 2004 by S. Tanaka (G–J, P–R); both lakes are in Hida Mountain Range, Honshu Island, Japan. A, parthenogenetic female, lateral view. B, head of parthenogenetic female. C, D, armature of postero-ventral and posterior region of valve. E, postabdomen. F–I, postabdominal claws of adults. J, postabdominal claw of juvenile. K, L, antenna I in lateral and distal view. M, N, distal portion of basal segment in posterior and anterior view. O, swimming seta. P, Q, ephippial female and postero-dorsal portion of its carapace. R, ephippium.
Figure 3 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 3. Daphnia curvirostris, large parthenogenetic female from Lake Glubokoe, Moscow area, European Russia, collected on August 9, 2004 by AAK. A, lateral view. B, caudal spine. C–E, head. F, G, armature of postero-ventral and posterior region of valve. H, postabdomen. I, J, postabdominal claw. K, L, antenna I in lateral and posterior view.
Figure 5 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 5. Daphnia curvirostris from Lake Glubokoe, Moscow area, European Russia, collected on September 9, 2004 by N. N. Smirnov. A, B, ephippial female and its postero-dorsal region. C, fresh ephippium. D, adult male. E, male head. F, G, armature of ventral margin of valve. H, armature of posterior portion of valve. I, J, postabdomen and abdomen. K, antenna I. L, antenna II. M, N, limb I and its distal portion. O, armature of distal portion of largest seta of outer distal lobe. P, innerdistal portion of limb II.
Figure 2 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 2. Mapping the characters of chromosome number and postabdominal claw morphology onto the Daphnia ND2 consensus tree (Fig. 1). A, the left cladogram shows the evolution of chromosome number. Black line denotes 2n = 22, white line denotes 2n = 20 and dot line denotes 2n = 24. B, the right cladogram shows the evolution of postabdominal claw morphology. Black line denotes variable phenotype between the longispina-claw and pulex-claw types, white line denotes the longispina- claw type, dot line denotes the pulex-claw type and grey line denotes equivocal.
Figure 4 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 4. Daphnia curvirostris, appendages of parthenogenetic female from Lake Glubokoe, European Russia. A, coxal part of antenna II. B, distal portion of basal segment and basal portion of branches. C, distal portion of endopod. D, swimming seta. E, maxilla I. F, limb I: ODL indicates outer distal lobe; IDL indicates inner distal lobe. G–I, limb II, second seta on its inner-distal end, and gnathobase II. J–L, limb III, its inner-distal portion and filtering seta of gnathobase. M, N, limb IV and its inner-distal portion. O, limb V.
Figure 1 in A new divergent lineage of Daphnia (Cladocera: Anomopoda) and its morphological and genetical differentiation from Daphnia curvirostris Eylmann, 1887
Figure 1. ME bootstrap consensus tree of Daphnia ND2 sequences. The numbers on each branch show support values of the branch. Upper numbers indicate ME, and ML bootstrap support values for nucleotide sequences. Middle numbers indicate MP bootstrap support values and Bayesian clade credibility values for nucleotide sequences. Lower numbers indicate MP bootstrap support values and Bayesian clade credibility values for amino acid sequences. Asterisks indicate no support values.
Critical Assessment of RNA-Seq Differential Expression
<p><strong>Warden and Wu Preprint</strong>: <a href="https://www.biorxiv.org/content/10.1101/2024.02.10.579728v1">v1</a></p> <p>In general, this primarily focuses on the following types of comparisons:</p> <ol> <li>Cell line experiments with over-expression or knock-down to define a known causal gene, with processing starting with public reads.</li> <li>Processed TCGA (The Cancer Genome Atlas) data for breast cancer (BRCA) to compare gene expression by immunohistochemistry status (ER/ESR1, PR/PGR, or HER2/ERBB2).</li> </ol> <p>Differential expression methods include the following:</p> <ul> <li><em>edgeR (GLM)</em></li> <li><em>edgeR-robust (GLM)</em></li> <li><em>edgeR (QL)</em></li> <li><em>edgeR-robust (QL)</em></li> <li><em>DESeq1</em></li> <li><em>DESeq2</em></li> <li><em>limma-voom</em></li> <li><em>limma-trend (CPM)</em></li> <li><em>limma-trend (FPKM/RPKM)</em></li> <li><em>ANOVA (log2 FRPKM/RPKM)</em></li> </ul> <p>The most common preprocessing strategies include STAR, TopHat2, and Salmon. However, a limited amount of additional processing with HISAT2, kallisto, Bowtie2 (+eXpress), and Bowtie1 (+RSEM) is also provided.</p> <p>Most STAR and TopHat2 alignments use htseq-count for quantification, as well as running cuffdiff (for single variable 2-group comparisons). However, a limited amount of additional processing with featureCounts is also provided.</p> <p>Most STAR and TopHat2 alignments start with the public <strong>forward</strong> reads, even if paired-end data was available.</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.