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Genes associated with plant growth-promoting traits (PGPTs) in acidobacteriota MAGs
<p>The prevalence and abundance of Acidobacteriota raise concerns about their ecological function and metabolic activity in the environment. Studies have reported the potential of some members of Acidobacteriota to interact with plants and play a significant role in biogeochemical cycles. However, their role in this context has not been extensively studied. Here, we performed a comprehensive genomic analysis of 758 metagenome-assembled genomes (MAGs) of Acidobacteriota, revealing a high frequency of plant growth-promoting traits (PGPTs) genes.</p>
Nine years of warming and nitrogen addition in the Tibetan grassland promoted loss of soil organic carbon but did not alter the bulk change of chemical structure
<p>Understanding the changes in soil organic carbon (SOC) storage and chemical stabilization dynamics is important for accurately predicting ecosystem C sequestration and/or potential C loss, but the relevant information, especially for the intervention of environmental controls on grassland soil is limited in Tibetan plateau regions. Here we used a 9-year two-way factorial experiment involving warming with open top chambers (+1.80 °C in the daytime and +0.77 °C in the nighttime at the soil surface) and multilevel nitrogen (N) enrichment treatments (0, 5, 10, and 15 g m<sup>-2</sup> year<sup>-1</sup>) in the Tibetan plateau to investigate the changes in SOC pool size and chemical structure. 9-year warming treatment significantly decreased SOC stock in the Tibetan grassland. We observed decreasing SOC concentrations which may be related to changes in the C degrading enzymes. Surprisingly, the SOC molecular structure remained unchanged in all N enrichment and warmed plots, suggesting that both treatments had affected all forms of SOC, from simple and complex polymeric in a similar way. Our results suggest that long-term warming stimulates soil C loss but no preference in SOC loss with different chemical structure.</p>
Figure 1 in Do mismatched genitalia promote mechanical isolation in syntopic species of Phalloceros fishes (Poeciliidae)?
Figure 1. Interspecific differences in genitalia of mature individuals of Phalloceros anisophallos and Phalloceros leptokeras. A, B, ventral views of female urogenital papillae of P. anisophallos (A) and P. leptokeras (B). Notice that the papilla is turned to the right from the perspective of the fish and points somewhat distally towards the tail in P. anisophallos, and is turned to the left and points somewhat laterally in P. leptokeras. C, D, lateral view of the distal portion of the gonopodia with the skin removed of P. anisophallos (C) and P. leptokeras (D). These schematic drawings simply depict the generalized morphologies of the genitalia for each species and thus do not reflect any single museum specimen.
Figure 3 in Do mismatched genitalia promote mechanical isolation in syntopic species of Phalloceros fishes (Poeciliidae)?
Figure 3. Among-individual variation in the presence/absence of dark lateral spots and the morphology of adult female papillae in Phalloceros anisophallos and Phalloceros leptokeras from the Parati-Mirim River in relationship to molecular barcode information. The barcode sequences for each specimen are listed at the bottom and correspond to mitochondrial (COI) and nuclear (MG1) DNA haplotypes. Based on the orientation of genital papillae, these specimens were initially identified as follows: P. anisophallos = MNTI 14559, 14553 and 10679; and P. leptokeras = MNTI 10684 and 10680. Note that morphologically and molecularly based species identifications for individual MNTI 14559 conflicted with each other, probably owing to an apparently aberrant papilla (see main text for more discussion). The size of the specimens corresponds to the standard length (SL), measured with digital callipers from the tip of the snout to the posterior margin of the hypural plate.
Figure 2 in Do mismatched genitalia promote mechanical isolation in syntopic species of Phalloceros fishes (Poeciliidae)?
Figure 2. Bayesian mitochondrial (mtDNA) and nuclear (nDNA) gene trees, showing the inferred relationships among haplotypes of Phalloceros anisophallos and Phalloceros leptokeras from the Parati-Mirim River and other localities. A, mtDNA tree for the COI sequences. B, nDNA tree for the MG1 sequences. Shaded names refer to samples misidentified based on morphological criteria (see Materials and Methods). Numbers in parentheses represent the number of identical haplotypes. Other species of Phalloceros were included as reference samples, and Cnesterodon decemmaculatus and Poecilia vivipara were used to root the trees. Phalloceros anisophallos and Phalloceros leptokeras are sympatric in the Parati-Mirim and Japuíba rivers. São Roque and Paquequer correspond to the type localities of P. anisophallos and P. leptokeras, respectively (Lucinda 2008). Numbers above each branch are the estimated Bayesian posterior probabilities.
Negative density-regulated contest performance promotes conflict resolution in a tree lizard
<p>This project includes the raw data of the research article 'Negative density-regulated contest performance promotes conflict resolution in a tree lizard' by Hsu et al.</p> <p>Data are in the file <code>negative-density-regulated-contest-performance.ods</code> (a OpenDocument spreadsheet). Download and open it by using spreadsheet software (e.g. Microsoft Office Excel, Libreoffice Calc)</p> <p>Sheet <code>covariates by population</code></p> <table> <thead> <tr> <th>Column</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>Site</td> <td>Lizard population</td> </tr> <tr> <td>log.female.over.male.ratio</td> <td>Natural logarithm of sex ratio (famel over male)</td> </tr> <tr> <td>n.injured</td> <td>Number of injured males</td> </tr> <tr> <td>n.not.injured</td> <td>Number of not injured males</td> </tr> <tr> <td>injury.ave</td> <td>Injury ratio</td> </tr> <tr> <td>selectDiff</td> <td>Standardized selection differential of male snout-vent length</td> </tr> <tr> <td>Comp.1</td> <td>1st principle component of habitat composition</td> </tr> <tr> <td>Comp.2</td> <td>2nd principle component of habitat composition</td> </tr> <tr> <td>Comp.3</td> <td>3rd principle component of habitat composition</td> </tr> <tr> <td>Comp.4</td> <td>4th principle component of habitat composition</td> </tr> <tr> <td>invSimpsonTrapAbundance</td> <td>Food items (inverse Simpson index) in item abundance from pitfall trap</td> </tr> <tr> <td>invSimpsonTrapWeight</td> <td>Food items (inverse Simpson index) in item dry mass from pitfall trap</td> </tr> <tr> <td>totalTrapWeight</td> <td>Total dry mass of food in pitfall trap (g)</td> </tr> <tr> <td>invSimpsonStomachAbundance</td> <td>Dietary breadth (inverse Simpson index) in abundance from stomach items</td> </tr> <tr> <td>invSimpsonStomachWeight</td> <td>Dietary breadth (inverse Simpson index) in dry mass from stomach items</td> </tr> <tr> <td>totalStomachWeight</td> <td>Total dry mass of items in stomach (g)</td> </tr> </tbody> </table> <p>Sheet <code>covariates by population and sex</code></p> <table> <thead> <tr> <th>Column</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>Site</td> <td>Lizard population</td> </tr> <tr> <td>Sex</td> <td>Sex</td> </tr> <tr> <td>density</td> <td>Number of lizard in 1250 m^2</td> </tr> </tbody> </table> <p>Sheet <code>stage fight</code></p> <table> <thead> <tr> <th>Column</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>Site</td> <td>Lizard population</td> </tr> <tr> <td>resident (SVL)</td> <td>Snout-vent length of resident lizard</td> </tr> <tr> <td>intruder (SVL)</td> <td>Snout-vent length of intruder lizard</td> </tr> <tr> <td>max.aggresive</td> <td>Resident highest agressive behavior</td> </tr> <tr> <td>is.R.win</td> <td>Resident as winner</td> </tr> <tr> <td>rScore</td> <td>Rank level of resident highest agressive behavior</td> </tr> </tbody> </table> <p>Sheet <code>bite force</code></p> <table> <thead> <tr> <th>Column</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>Site</td> <td>Lizard population</td> </tr> <tr> <td>Sex</td> <td>Sex</td> </tr> <tr> <td>Body weight</td> <td>Lizard body weight (g)</td> </tr> <tr> <td>Head length</td> <td>Lizard head length (mm)</td> </tr> <tr> <td>Head width</td> <td>Lizard head width (mm)</td> </tr> <tr> <td>Head height</td> <td>Lizard head height (mm)</td> </tr> <tr> <td>SVL</td> <td>Lizard snout-vent length (mm)</td> </tr> <tr> <td>Bite Force</td> <td>Lizard bite force (N)</td> </tr> </tbody> </table> <p>Abstract</p> <ol> <li>Territoriality is a behavioral adaptation resulting from intraspecific competition and reflects the strategy of how individuals share limited resources in the environment. As a consequence, territorial contests and levels of aggressiveness are strongly influenced by population density.</li> <li>The positive relationship between population density and the intensity of intraspecific competition may appear straightforward. However, empirical evidence regarding this association remains inconclusive. This ambiguity may be attributed to studies that have predominantly focused on specific fight-associated traits while overlooking the comprehensive assessment of multiple phenotypic characteristics.</li> <li>To examine the effects of population density and other ecological factors on the variation in fight behavior as well as fight-associated morphology and performance. We conducted population surveys and behavioral experiments using the Swinhoe’s tree lizard across eight populations.</li> <li>Our findings revealed that males from higher-density populations tended to engage in less intense fights and exhibited a weaker resident advantage in fights, which coincided with our findings on lower rates of injuries, weaker bite forces, and smaller body sizes (and vice versa). Male-specific plasticity in fight behavior, morphology, and performance along a density gradient suggests different evolutionary equilibria in territoriality influenced by local costs and benefits.</li> <li>Our study supports the significant role of negative density dependence as a fundamental regulator of eco-evolutionary dynamics. The observed phenotypic plasticity emphasizes the importance of ecological and social factors in shaping ontogenetic growth and life-history strategies. Our findings provide a basis for future investigations into pace-of-life syndromes and shed light on how phenotypic adaptation may shape population structure.</li> </ol>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Merged datasets
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (5/5).<br> Merged datasets: Run 1 cDNA 1 + Run 1 cDNA 2 + Run 2 cDNA 1 + Run 2 cDNA 2</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 1 cDNA 1
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (1/5).<br> RUN 1(/2), cDNA 1(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 2 cDNA 2
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (4/5).<br> RUN 2(/2), cDNA 2(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 2 cDNA 1
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (3/5).<br> RUN 2(/2), cDNA 1(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 1 cDNA 2
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (2/5).<br> RUN 1(/2), cDNA 2(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
iGEM Leiden 2023 - Promoter characterization
<p>Promoter characterization data in <em>Methylobacterium extorquens</em> AM1 of three growth assay experiments (fluorescence and OD measured over time). </p>
Homotypic motifs from 5 databases in the promoters of 21 plant species
<p><strong>What is this about:</strong></p> <p>This project encompasses multiple plant species, primarily employing tools like FIMO and PMET index to search for homotypic motifs in the promoters across various plant species. We selected five different sources of motifs: <strong>CIS-BP2</strong>, <strong>Franco-Zorrilla et al. 2014</strong>, <strong>Jaspar plants non redundant 2022</strong>, <strong>PlantTFDB</strong> and <strong>Plant Cistrome DB</strong>.</p> <p>Our research delves into an extensive analysis of gene expression regulatory elements, aiming to unravel the mechanisms of plant gene expression regulation. For this purpose, we have pre-calculated a vast amount of data in order to identify promoter patterns that consistently appear across different species. These promoter patterns potentially play fundamental and crucial regulatory roles in each species.</p> <p><strong>How to use it:</strong></p> <p>All data are prepared for PMET-Shiny app: <a href="https://github.com/duocang/PMET-Shiny-App">https://github.com/duocang/PMET-Shiny-App</a>.</p> <p>After downloading, all files are unzipped and put in the folder of <em><strong>data/indexing</strong></em> of PMET-Shiny.</p>
Defining signals that promote human alveolar type I differentiation-Supplementary Figures
<p><strong>Supplemental Figure 1. Human serum robustly promotes alveolar type I differentiation in part through BMP signaling pathway</strong></p><ol><li>Schematic for generating ATI spheroids using human serum.</li><li>The inhibition of <i>AGER</i> gene expression by Noggin under ADM containing human serum (*<i>P</i> < 0.05 and **<i>P</i> < 0.01).</li></ol><p>C-E. Immunostaining for SFTPC and AGER for ATII spheroids treated with ADM without human serum, ADM and ADM plus Noggin. Representative of three independent experiments. Scale bar: 50µm.</p><ol><li>Quantification of SFTPC and AGER for ATII spheroids treated with ADM without human serum, ADM and ADM plus Noggin. Representative of three independent experiments.</li></ol><p><strong>Supplemental Figure 2. BMP4 promoted </strong><i><strong>HOPX</strong></i><strong> transcript expression in ATII spheroids in a BMP concentration-dependent manner. Representative of three independent experiments</strong></p><p><strong>Supplemental Figure 3. CDKN1A and CLDN4 expression in ATII spheroids cultured under hATIIM, hATIIM + BMP4 and hATIDM.</strong></p><ol><li>Schematic for CDKN1A and CLDN4 expression using ATII spheroids under hATIIM, hATIIM + BMP and hATIDM.</li><li>The <i>CDKN1A</i> and <i>CLDN4</i> transcript expression under hATIIM, hATIIM + BMP and hATIDM in three biological samples and triplicate technical repeat.</li></ol><p>C-E. Immunostaining for CDKN1A, SFTPC and AGER for ATII spheroids cultured with hATIIM, hATIIM + BMP and hATIDM. Representative of four independent experiments. Scale bar: 50µm.</p><p>F. Quantification of CDKN1A for ATII spheroids treated with hATIIM, hATIIM + BMP and hATIDM. Representative of four independent biological samples.</p><p><strong>Supplemental Figure 4. The ATI differentiation efficiency comparison of ATII spheroids and DLOs using hATIDM and sc-RNA Sequencing</strong></p><ol><li>The relative expression of <i>SFTPC</i>, <i>AGER</i> and <i>HOPX</i> using sc-RNA sequencing from http://ipfcellatlas.com/</li></ol><p> B-D. The relative expression of <i>SFTPC</i>, <i>AGER</i> and <i>HOPX</i>from ATII spheroids and DLOs using hATIIM and hATIDM, </p>
Transcripts of interviews and focus group interviews pertaining to the perceived acceptance and feasibility of the KaziKidz health promotion intervention by educators and caregivers in schools from South Africa
<p>Transcripts used to perform a thematic analysis of the lived experiences, acceptability and perceived feasibility of school principals, educators and caregivers from public primary schools in South Africa that participated in the KaziKidz health promotion intervention.</p><p>It encompasses anonymized verbatim transcripts from four semi-structured interviews with principals from the four participating schools as well as six focus group interviews, three with teachers and three with caregivers.</p>
Implementing an Education- and Health System Task-shifting Approach for Child Mental Health Promotion in Uganda
ClinicalTrials.gov study NCT06275672. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Milk Biofortification Promotes Health Benefits in Institutionalized Elderly
ClinicalTrials.gov study NCT02980094. IPD Sharing: NO. Countries: 1. Publications: 5.
Physical Activity in Health Promotion Course on the Physical Activity Habits
ClinicalTrials.gov study NCT05711251. IPD Sharing: YES. Countries: 1. Publications: 2.
Theta Burst Stimulation to Promote Motor Re-education in Tetraplegia
ClinicalTrials.gov study NCT03277521. IPD Sharing: NO. Countries: 1. Publications: 1.
Active and Healthy Kids in Telemark - a School Based Health Promoting Intervention
ClinicalTrials.gov study NCT03906851. IPD Sharing: NO. Countries: 1. Publications: 5.
ScienceDex guides
Understand access before you commit
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.