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The pan-gene, pan-genome, and SV-eQTL dataset for A2 and AD1 cotton.
Open the record for dataset details and reuse information.
FIGURE 3 in Three new species of Campanulaceae from the Pan-Himalaya
FIGURE 3. Illustration of Campanula microphylloidea: 1. plant; 2. branches with flowers; 3. dissected flower; 4. densely puberulent leaf.
FIGURE 2 in Three new species of Campanulaceae from the Pan-Himalaya
FIGURE 2. Illustration of Campanula rotata: 1. plant with rotate flowers; 2. rotate flower; 3. stamen.
FIGURE 6 in A taxonomical revision of Ilex (Aquifoliaceae) in the Pan-Himalaya and unraveling its distribution patterns
FIGURE 6. Photographs of pyrenes of Ilex rotunda Thunberg showing the dorsal side. a–e, The pyrenes smooth or obscurely striate, esulcate. a, from Tengchong, SW Yunnan; b, from Lincang, SW Yunnan; c, from Luchuan, C Yunnan; d, from Huili, S Sichuan; e, from Qingzhen, C Guizhou. f–l, The pyrenes distinctly 3-striate, 2-sulcate. f, from Fangjing Shan, NE Guizhou; g, from Yanshan, SE Yunnan; h, from Pingbian, SE Yunnan; i, from Xichou, SE Yunnan; j, from Fangcheng, S Guangxi; k, from Taiwan; l, from Japan. Scale bar = 0.2 cm.
FIGURE 4. Ilex gansuensis D. Y. Hong, a in A taxonomical revision of Ilex (Aquifoliaceae) in the Pan-Himalaya and unraveling its distribution patterns
FIGURE 4. Ilex gansuensis D. Y. Hong, a new species from SE Gansu of China: a. a branch; b. a fruit; c. a pyrene.
FIGURE 1 in A taxonomical revision of Ilex (Aquifoliaceae) in the Pan-Himalaya and unraveling its distribution patterns
FIGURE 1. Variation in the number of spines on leaves from a single shoot of Ilex bioritsensis Hayata. The voucher: China, Chongqing, Jinfo Shan, J. H. Xiong & Z. L. Zhou 90574 (PE). a, two spines on each side; b, two on right, while four on left; c, five on right, while four on left. Scale bar = 1 cm.
Pan-Cancer T cell atlas from "The combined use of scRNA-seq and network propagation highlights key features of pan-cancer Tumor-Infiltrating T cells" (https://doi.org/10.1371/journal.pone.0315980)
<p>The scRNA-seq data were collected from previously published datasets (GSE140228, GSE139555, GSE155698, GSE121636, and GSE139324), adhering to the following selection criteria: 1) presence of T cells, 2) treatment-naïve patients, 3) solid tumors, and 4) inclusion of at least tumor and blood samples.<br>Each scRNA-seq dataset underwent separate preprocessing in R (v4.0.2). We filtered out cells from the original count matrices that had fewer than 200 genes detected or more than 10% mitochondrial UMI counts and we only kept genes detected in at least 3 cells. Then, we applied Seurat (v4.0.5) with default parameters for count data normalization and scaling. Each cell was assigned a cell cycle score using the CellCycleScoring function and we computed the difference between the G2M and S phase scores. This approach allows for the separation of non-cycling from cycling cells while minimizing the differences in cell cycle phase among proliferating cells. The SelectIntegrationFeatures function was ran with the nfeatures parameter set to 3,000 before merging all samples from each dataset. These integration features were then used for Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Clustering was performed using the Louvain algorithm with the resolution parameter set to 2.0 for all datasets. Finally, T cells were isolated based on CD3D and CD3G genes expression (CD3D or CD3G expression level > 0).</p> <p>To integrate heterogeneous data from different sources, a two-step procedure was applied. We first concatenated all datasets together and ran the scaling and PCA steps based on the top 3,000 highly variable genes identified by the FindVariableFeatures function with the “vst” method. Harmony was applied for batch effect correction then UMAP and clustering using the Louvain algorithm with the resolution parameter set to 2.0 were performed on the harmony reduction. Examining the result from the first clustering run, we identified contamination clusters and clusters that arose from unwanted factors: we removed the contamination clusters including low quality cells highly expressing marker genes associated with apoptosis and tissue dissociation operation, pancreatic acinar cells (expressing PRSS1, CLPS, PNLIP and CTRB1 among others), myeloid cells (expressing CD68) and B cells (expressing CD79A). Then, we performed the second run of integration and clustering excluding immunoglobulin, ribosome-protein-coding, and T cell receptor (TCR) genes (gene symbol with string pattern "^IGK|^IGH|^IGL|^IGJ|^IGS|^IGD|IGFN1", "^RP([0–9]+-|[LS])", and "^TRA|^TRB|^TRG" respectively) from the top 3,000 highly variable genes and regressing out the cell cycle difference effect as well as the percentage of mitochondrial UMI counts. Harmony (v0.1.0) was applied again for batch effect correction and UMAP was performed on the harmony reduction.<br>T cell subtypes identification and annotation was performed by clustering cells using the Louvain algorithm with the resolution parameter set to 4.1 after iterative testing from 3.5 to 5.0 by 0.1 (more granular than default), computing clusters signatures based on differential gene expression using the FindAllMarkers function with the “MAST” method and interrogating known gene markers expression. A resolution value of 4.1 was notably found to be the lowest resolution value enabling the correct separation of proliferating CD4+ T cells from proliferating CD8+ T cells.</p>
Dataset and codes for 'Enhancing glymphatic fluid transport by pan-adrenergic inhibition suppresses epileptogenesis in male mice'
<p>This is the code and dataset repository for the publication entitled 'Enhancing glymphatic fluid transport by pan-adrenergic inhibition suppresses epileptogenesis in male mice' on Nature Communications, 2024. Author list: </p> <p>Qian Sun<sup>†</sup>, Sisi Peng<sup>†</sup>, Qiwu Xu, Pia Weikop, Rashad Hussain, Wei Song, Maiken Nedergaard§, Fengfei Ding§</p>
The data of the mesh used in: Pan M, Zou R, Jüttler B. Algorithms and Data Structures for Cs-smooth RMB-splines of Degree 2s+ 1. Computer Aided Geometric Design, 2024: 102389.
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Data from: A review of the defining chemical properties of soda lakes and pans: an assessment on a large geographic scale of Eurasian inland saline surface waters
The aim of this study is to evaluate the definition of water chemical type, with particular attention to soda brine characteristics by assessing ionic composition and pH values on a large geographic scale and broad salinity (TDS) range of Eurasian inland saline surface waters, in order to rectify the considerable confusion about the exact chemical classification of soda lakes and pans. Data on pH and on the concentration of eight major ions were compiled into a database drawn from Austria, China, Hungary, Kazakhstan, Mongolia, Russia, Serbia, and Turkey. The classification was primarily based on dominant ions exceeding an equivalent percentage of 25 (> 25e%) of the total cations or anions, and the e% rank of dominant ions was also identified. We identified four major types: waters dominated by (1) Na-HCO3 (10.0%), (2) Na-HCO3 + CO3 (31.4%), (3) Na-Cl (45.9%), and (4) Na-SO4 (12.7%), considering only the first ion by e% rank. These major types can be divided into 30 subtypes in the dataset, taking into account the e% rank of all dominant ions. The major and subtypes of soda brine can be divided into "Soda" and "Soda-Saline" types. "Soda type" when Na+ and HCO3– + CO32– are the first in the rank of dominant ions (> 25e%), and "Soda-Saline type" when Na+ is the first in the rank of dominant cations and the sum of HCO3– + CO32– concentration exceeds 25e%, but it is not the first in the rank of dominant anions. Soda-saline type can be considered as a separate evolutionary stage between Soda and Saline types respect to the geochemical interpretation by saturation indexes of brines. The obtained overlapping ranges in distribution demonstrate that a pH measurement alone is not a reliable indicator to classify the permanent alkaline "soda type" and various other types of temporary alkaline waters.
Colour pan-traps often catch less when there are more flowers around
<p>When assessing changes in populations of species it is essential that the methods used to collect data have some level of precision and preferably also good accuracy. One commonly used method to collect pollinators is colour pan-traps, but this method has been suggested to be biased by the abundance of surrounding flowers. The present study evaluated the relationship between pan-trap catches and the frequency of flowers on small (25 m2) and large (2-6 ha) spatial scales. If pan-traps work well, one should assume a positive relationship, i.e. more insects caught when they have more food. However, in contrast, we found that catches in pan-traps were often negatively affected by flower frequency. Among the six taxa evaluated, the negative bias was largest in Vespoidea and Lepturinae, while there was no bias in solitary Apoidea (Cetoniidae, Syrphidae and social Apoidea were intermediate). Furthermore, red flowers seemed to contribute most to the negative bias. There was also a tendency that the negative bias differed within the flight season and that is was higher when considering the large spatial scale compared to the small one. To conclude, pan-trap catches may suffer from a negative bias due to surrounding flower frequency and colour. The occurrence and magnitude of the negative bias was context and taxon dependent, and therefore difficult to adjust for. Thus, pan-traps seems less suited to evaluate differences between sites and the effect of restoration, when gradients in flower density is large. Instead, it seems better suited to monitor population changes within sites, and when gradients are small.</p>
FIGURE 2. Actinopyga bannwarthi Panning, 1944. Inhaca. A in Additions to the aspidochirotid, molpadid and apodid holothuroids (Echinodermata: Holothuroidea) from the east coast of southern Africa, with descriptions of new species
FIGURE 2. Actinopyga bannwarthi Panning, 1944. Inhaca. A. Rods from dorsal body wall; B. same from ventral body wall; C. podial rods; D. tentacle rods; E. part of calcareous ring. (A, B & C scale a)
The chicken pan-genome reveals gene content variation and a promoter region deletion in IGF2BP1 affecting body size
<p></p><p>Domestication and breeding have reshaped the genomic architecture of chicken, but the retention and loss of genomic elements during these evolutionary processes remain unclear. We present the first chicken pan-genome constructed using 664 individuals, which identified an additional ∼66.5 Mb sequences that are absent from the reference genome (GRCg6a). The constructed pan-genome encoded 20,491 predicated protein-coding genes, of which higher expression level are observed in conserved genes relative to dispensable genes. Presence/absence variation (PAV) analyses demonstrated that gene PAV in chicken was shaped by selection, genetic drift, and hybridization. PAV-based GWAS identified numerous candidate mutations related to growth, carcass composition, meat quality, or physiological traits. Among them, a deletion in the promoter region of IGF2BP1 affecting chicken body size is reported, which is supported by functional studies and extra samples. This is the first time to report the causal variant of chicken body size QTL located at chromosome 27 which was repeatedly reported. Therefore, the chicken pan-genome is a useful resource for biological discovery and breeding. It improves our understanding of chicken genome diversity and provides materials to unveil the evolution history of chicken domestication.</p><p></p>
Figure 3. Chronogram. The maximum clade credibility tree amongst 9000 in Vicariance and convergence in Magellanic and New Zealand long-looped brachiopod clades (Pan-Brachiopoda: Terebratelloidea)
Figure 3. Chronogram. The maximum clade credibility tree amongst 9000 trees from an uncorrelated lognormal relaxed clock analysis of the rDNA alignment. Nodes are labelled A–R and show mean node ages and 95% highest posterior density (HPD) ranges as wide black bars. See Table 1 for details of SDmean, 95% HPD confidence limits of mean ages, descriptions of nodes and of mean age agreement with external ages. Vertical lines labelled NZ (New Zealand), MAG (Magellanic), Laq (laqueoid) and Short (short-looped terebratulidine) mark the respective clades and the proximate and more distant outgroups. Evolutionary model for dating analysis: 18 taxa, 2833 sites, general time reversible with estimated frequency of invariant sites and gamma rate distribution (four rate categories) with empirical base frequencies; uncorrelated lognormal distribution. Priors: substitution rates, Jefferies; site model alpha and invariant, Normal, mean = 0.7, SD = 0.1, initial = 0.7; tree model root height, lognormal logx mean = 2.39, SD = 0.5; defined taxon sets, default tree prior. Markov chain Monte Carlo chain 107 cycles, sampled every 103. TreeAnnotator was used to identify the maximum clade credibility tree of 9000 trees after 1001 trees were discarded as burnin.
Figure 5 in Vicariance and convergence in Magellanic and New Zealand long-looped brachiopod clades (Pan-Brachiopoda: Terebratelloidea)
Figure 5. Scanning electron microscope images of transverse sections of dorsal shells. Images are from near the middle of each section and therefore are approximately perpendicular to the shell anterior–posterior axis. Labels indicate primary layer (PL) and secondary layer (SL). Measurements are from various mid-section locations, not only those in images. Scale bars: A–C, E, F = 200 Mm, D = 100 Mm. If viewed on screen or printed as a full-page image the secondary fibres may appear too small to be clearly visible. Therefore the original figures (~760 dpi) are also available in Appendix S2A–F. A, Coptothyris sp. Shell total thickness 748–1130 Mm (ribs), 474–527 Mm (grooves). Mean rib height 632 ± 193 Mm (N = 7). PL thickness 49.4–64.9 Mm (ribs), 24.4–26.6 Mm (grooves). SL thickness 757–951 Mm (ribs), 472–480 Mm (grooves). B, Terebratalia transversa. Shell total thickness 883–982 Mm (ribs), 580–784 Mm (grooves). Mean rib height 250 ± 89 Mm (N = 8). PL thickness 60–75.3 Mm (ribs), 44.2–60.7 Mm (grooves). SL thickness 850–929 Mm (ribs), 635–684 Mm (grooves). C, Magellania venosa. Shell total thickness 700–960 Mm. PL thickness 32.1–41.9 Mm. SL thickness 654–918 Mm. D, Terebratulina retusa. Shell total thickness 227–254 Mm (ribs), 163–173 Mm (grooves). PL thickness 30.6–64 Mm (ribs), 7.7–12.9 Mm (grooves). SL thickness 170–189 Mm (ribs), 136–164 Mm (grooves). E, Terebratella dorsata. Shell total thickness 873–973 Mm (ribs), 803–848 Mm (grooves). Mean rib height 79.1 ± 18.4 Mm (N = 6). PL thickness 42–62.5 Mm (ribs), 28.6–39.1 Mm (grooves). SL thickness 850–929 Mm (ribs), 768–797 Mm (grooves). F, Terebratella sanguinea. Shell total thickness 338–414 Mm (ribs), 281–333 Mm (grooves). Mean rib height 56.9 ± 14.6 Mm (N = 3). PL thickness 31.4–46.5 Mm (ribs), 26.3–36.3 Mm (grooves). SL thickness 361–365 Mm (ribs), 259–285 Mm (grooves).
Figure 2 in Vicariance and convergence in Magellanic and New Zealand long-looped brachiopod clades (Pan-Brachiopoda: Terebratelloidea)
Figure 2. Maximum likelihood (ML) phylogram based on the cytochrome oxidase subunit 1 (cox1; all nucleotide sites) alignment, with bootstrap %. In the Akaike information criterion-selected best-fit ML model (Hasegawa-Kishino-Yano, with estimated frequency of invariable sites, Pinvar = 0.45 and gamma distribution of rates, shape parameter 0.92). Labels as in Figure 1.
Figure 1 in Vicariance and convergence in Magellanic and New Zealand long-looped brachiopod clades (Pan-Brachiopoda: Terebratelloidea)
Figure 1. Maximum likelihood (ML) phylogram based on rDNA sequences. Taxa with ribbed shells have underlined names. Vertical lines labelled NZ (New Zealand), MAG (Magellanic) and Laq (laqueoid) mark the respective ingroup clades and the outgroup. ML tree constructed by heuristic search with tree bisection-reconnection branch exchange, rooted with laqueoid outgroups and using the Akaike information criterion-selected alignment-specific general time reversible ML model with gamma and invariant site corrections, gamma shape = 0.78 Pinvar = 0.80. With bootstrap support (%) based on 1000 pseudoreplicates using ML distances analysed by BioNJ. The maximum parsimony and ML trees had identical topology and similar bootstrap % (parsimony length = 1169, consistency index = 0.95, retention index = 0.84).
Figure 4 in Vicariance and convergence in Magellanic and New Zealand long-looped brachiopod clades (Pan-Brachiopoda: Terebratelloidea)
Figure 4. Macrophotographs of Terebratella spp. individuals. A, B, dorsal and anterior views of an individual of Terebratella dorsata. C, dorsal view of a second individual of Terebratella dorsata. D, E, dorsal and anterior views of an individual of Terebratella sanguinea. F, dorsal view of a second individual of Terebratella sanguinea. Scale bars = 1.0 cm.
Figure 6 in Vicariance and convergence in Magellanic and New Zealand long-looped brachiopod clades (Pan-Brachiopoda: Terebratelloidea)
Figure 6. Growth trajectories. Scattergrams of length (L) and width (W) in samples of Magellania venosa (N = 31), Terebratella dorsata (N = 36) and Terebratella sanguinea (N = 63), with linear regression lines (not constrained to pass through zero). Regression accounts for 82 to 92% of the size variation. See text for details. t-tests for differences in slope found a significant difference (P = 0.01) between Magellania venosa and Terebratella dorsata and between each of them and Terebratella sanguinea (P << 0.001).
Data from: Genome-wide investigation of the multiple origins hypothesis for deep-spawning kokanee salmon (Oncorhynchus nerka) across its pan-Pacific distribution
<p>Salmonids have emerged as important study systems for investigating molecular processes underlying parallel evolution given their tremendous life history variation. Kokanee, the resident form of anadromous sockeye salmon (<i>Oncorhynchus nerka</i>), have evolved multiple times across the species' pan-Pacific distribution, exhibiting multiple reproductive ecotypes including those that spawn in streams, on lake-shores, and at lake depths >50 meters. The latter has only been detected in five locations in Japan and British Columbia, Canada. Here, we investigated the multiple origins hypothesis for deep-spawning kokanee, using 9,721 SNPs distributed across the genome analyzed for the vast majority of known populations in Japan (Saiko Lake) and Canada (Anderson, Seton, East Barrière Lakes) relative to stream-spawning populations in both regions. We detected 397 outlier loci, none of which were robustly identified in paired-ecotype comparisons in Japan and Canada independently. Bayesian clustering and principal components analyses based on neutral loci revealed six distinct clusters, largely associated with geography or translocation history, rather than ecotype. Moreover, a high level of divergence between Canadian and Japanese populations, and between deep- and stream-spawning populations regionally, suggest the deep-spawning ecotype independently evolved on the two continents. On a finer level, Japanese kokanee populations exhibited low estimates of heterozygosity, significant levels of inbreeding, and reduced effective population sizes relative to Canadian populations, likely associated with transplantation history. Along with preliminary evidence for hybridization between deep-spawning and stream-spawning ecotypes in Saiko Lake, these findings should be considered within the context of on-going kokanee fisheries management in Japan.</p>
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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.