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Dataset results
14 results for “vertebrate brain”
Joint embedding of vertebrate brain single-cell RNA-Seq using sequence or structure
<p>Embeddings of single-cell RNA-Seq data from three adult vertebrate brain datasets into Orthogroup feature space or Structural cluster feature space. Orthogroups were generated using OrthoFinder v5.5.0; Structural clusters were assigned by using FoldSeek to cluster AlphaFold-v4 structural predictions.<br> <br> The three datasets used as the basis for these embeddings were:</p> <ul> <li>sample <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3768152">"Brain8"</a> from the <a href="https://www.frontiersin.org/articles/10.3389/fcell.2021.743421/full">Jiang et al. 2021</a> zebrafish cell atlas (files beginning with GSM3768152)</li> <li>sample <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2906405">"Brain1"</a> from the <a href="https://www.sciencedirect.com/science/article/pii/S0092867418301168#sec4">Han et al. 2018</a> mouse cell atlas (files beginning with GSM2906405)</li> <li>sample <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM6214268">"Xenopus_brain_COL65"</a> from the <a href="https://www.nature.com/articles/s41467-022-31949-2">Liao et al. 2022</a> Xenopus laevis adult cell atlas (files beginning with GSM6214268)</li> </ul> <p>For each dataset, we also generated a standardized cell type annotation file based on the author's originally provided cell type annotation data. The first column is the cell barcode for that species and the second column is the original study's cell type annotation for that cell.</p> <p>For the Xenopus brain data, we removed around ~18k cells that were not annotated in the original data to simplify data analyses - these are reflected in the files with the "subsampled" suffix. Subsampled versions of the data are also available for the joint embedding space (prefixed with "DrerMmusXlae").</p> <p>For the final datasets used in our analyses, we also provide features x cell matrices as .h5ad files for smaller file sizes and faster loading using Scanpy. </p> <p>For visualizing our UMAP plots of our top200 embedding space, we provide ".tsv" files with a variety of metrics and the x and y positions of each cell in the UMAP. See "DrerMmusXlae_adultbrain_FoldSeek_plotlydata.tsv" and "DrerMmusXlae_adultbrain_OrthoFinder_plotlydata.tsv"</p> <p>These data are part of the Arcadia Science Pub titled <a href="https://doi.org/10.57844/arcadia-vw5e-2670">"Comparing gene expression across species based on protein structure instead of sequence"</a>.</p>
Petrucco et al, Neural dynamics and architecture of the heading direction circuit in a vertebrate brain [Dataset]
<p>Data supporting the paper <a href="https://www.biorxiv.org/content/10.1101/2022.04.27.489672v1.full">Neural dynamics and architecture of the heading direction circuit in a vertebrate brain</a>. </p>
Supplementary Data Files from: A lamprey neural cell type atlas illuminates the origins of the vertebrate brain
<p><strong>Supplementary Data </strong><strong>1</strong></p> <p>Lamprey genome custom annotation files.</p> <p> </p> <p><strong>Supplementary Data 2</strong></p> <p><em>In situ</em> images produced in this study.</p>
Data from: Transcriptomic analysis of the lesser spotted catshark (Scyliorhinus canicula) pancreas, liver and brain reveals molecular level conservation of vertebrate pancreas function
Background: Understanding the evolution of the vertebrate pancreas is key to understanding its functions. The chondrichthyes (cartilaginous fish such as sharks and rays) have often been suggested to possess the most ancient example of a distinct pancreas with both hormonal (endocrine) and digestive (exocrine) roles. The lack of genetic, genomic and transcriptomic data for cartilaginous fish has hindered a more thorough understanding of the molecular-level functions of the chondrichthyan pancreas, particularly with respect to their "unusual" energy metabolism (where ketone bodies and amino acids are the main oxidative fuel source) and their paradoxical ability to both maintain stable blood glucose levels and tolerate extensive periods of hypoglycemia. In order to shed light on some of these processes, we carried out the first large-scale comparative transcriptomic survey of multiple cartilaginous fish tissues: the pancreas, brain and liver of the lesser spotted catshark, Scyliorhinus canicula. Results: We generated a mutli-tissue assembly comprising 86,006 contigs, of which 44,794 were assigned to a particular tissue or combination of tissues based on mapping of sequencing reads. We have characterised transcripts encoding genes involved in insulin regulation, glucose sensing, transcriptional regulation, signaling and digestion, as well as many peptide hormone precursors and their receptors for the first time. Comparisons to mammalian pancreas transcriptomes reveals that mechanisms of glucose sensing and insulin regulation used to establish and maintain a stable internal environment are conserved across jawed vertebrates and likely pre-date the vertebrate radiation. Conservation of pancreatic hormones and genes encoding digestive proteins support the single, early evolution of a distinct pancreatic gland with endocrine and exocrine functions in jawed vertebrates. In addition, we demonstrate that chondrichthyes lack pancreatic polypeptide (PP) and that reports of PP in the literature are likely due cross-reaction with PYY and/or NPY in the pancreas. A three hormone islet organ is therefore the ancestral jawed vertebrate condition, later elaborated upon only in the tetrapod lineage. Conclusions: The cartilaginous fish are a great untapped resource for the reconstruction of patterns and processes of vertebrate evolution and new approaches such as those described in this paper will greatly facilitate their incorporation into the rank of "model organism".
Data from: Automated deep-phenotyping of the vertebrate brain
Here we describe an automated platform suitable for large-scale deep-phenotyping of zebrafish mutant lines, which uses optical projection tomography to rapidly image brain-specific gene expression patterns in 3D at cellular resolution. Registration algorithms and correlation analysis are then used to compare 3D expression patterns, to automatically detect all statistically significant alterations in mutants, and to map them onto a brain atlas. Automated deep-phenotyping of a mutation in the master transcriptional regulator fezf2 not only detects all known phenotypes but also uncovers important novel neural deficits that were overlooked in previous studies. In the telencephalon, we show for the first time that fezf2 mutant zebrafish have significant patterning deficits, particularly in glutamatergic populations. Our findings reveal unexpected parallels between fezf2 function in zebrafish and mice, where mutations cause deficits in glutamatergic neurons of the telencephalon-derived neocortex.
Data from: Automated deep-phenotyping of the vertebrate brain
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Data from: Transcriptomic analysis of the lesser spotted catshark (Scyliorhinus canicula) pancreas, liver and brain reveals molecular level conservation of vertebrate pancreas function
Open the record for dataset details and reuse information.
Emergence of neuronal diversity during vertebrate brain development
GEO Series GSE158142. Danio rerio. 79 samples. Type: Expression profiling by high throughput sequencing.
Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain
GEO Series GSE105010. Danio rerio. 72 samples. Type: Expression profiling by high throughput sequencing; Other.
Data from: Why do endothermic vertebrates have bigger brains than ectothermic ones?
<p class="MsoNormal"><span>Endothermic vertebrates (birds and mammals) show much larger relative brain sizes than ectothermic ones. The gap is widely attributed to the evolution of endothermy itself, which makes sustained high body temperatures possible. However, other variables that emerged or proliferated after endothermy arose, in particular greater and more extended </span><span>parental </span><span>provisioning</span><span>, no doubt also contribute to this gap. </span><span>Here, we conducted a targeted comparison of lizards and precocial birds to estimate the relative contribution of these factors. B</span><span>oth taxa share large amniotic eggs, lack post-hatching provisioning, and have overlapping body temperatures. After statistically removing additional confounding variables, we found that the statistical effect of endothermy amounts to a near-tripling of brain size, and thus accounts for about half of the difference in brain size between lizards and birds in general. A separate analysis revealed that the effect of extended parental provisioning in birds is associated with a near-doubling of brain size. These results suggest that various processes that were enabled or facilitated by endothermy, in particular parental provisioning after </span><span>hatching or birth</span><span>, played an equally important role in the evolution of increased brain size among endotherms.</span></p>
Data from: Why do endothermic vertebrates have bigger brains than ectothermic ones?
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Convergent evolution of scavenger cell development at vertebrate brain borders
GEO Series GSE270486. Danio rerio; Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Evolution of CpH methylation in vertebrate brains
GEO Series GSE141609. Gallus gallus; Ornithorhynchus anatinus; Lethenteron camtschaticum; Danio rerio; Monodelphis domestica; Apis mellifera; Callorhinchus milii; Octopus bimaculoides; Branchiostoma lanceolatum. 11 samples. Type: Expression profiling by high throughput sequencing; Methylation profiling by high throughput sequencing.
Post-transcriptional characterization of the vertebrate aging brain sheds light on the origin of protein-transcript decoupling
GEO Series GSE236685. Nothobranchius furzeri. 16 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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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.