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138 results for “Mouse retina”
Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy
<p>Raman raw data for the paper "Biochemical Characterization of Mouse Retina of an Alzheimer’s Disease Model by Raman Spectroscopy"</p> <ul> <li>two datasets of Raman images from cross-sectional and en face mouse retinas without processing</li> </ul>
Spatial organization of the mouse retina at single cell resolution by MERFISH
<p><strong>Abstract:</strong><br> <br> The visual signal processing in the retina requires the precise organization of diverse neuronal types working in concert. While single-cell omics studies have identified more than 120 different neuronal subtypes in the mouse retina1, little is known about their spatial organization. Here, we generated the first single-cell spatial atlas of the mouse retina using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We profiled over 390,000 cells and identified all major cell types and nearly all subtypes through the integration with reference single-cell RNA sequencing (scRNA-seq) data. Our spatial atlas allowed simultaneous examination of nearly all cell subtypes in the retina, revealing 8 previously unknown displaced amacrine cell subtypes and establishing the first connection between the molecular classification of many cell subtypes and their spatial arrangement. Furthermore, we identified spatially dependent differential gene expression between subtypes, suggesting the possibility of functional tuning of neuronal types based on location.<br> <br> <strong>Data description:</strong><br> 1. VZA105a_integrated_368genes.h5ad<br> This file contains the raw MERFISH count matrix for four samples with 368 gene features. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.</p> <p><br> 2. VA45_integrated.h5ad<br> This file contains the raw MERFISH count matrix for six samples with 500 gene features. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.<br> <br> 3. merfish_impute.h5ad<br> This file contains the imputed count matrix for ten samples. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.<br> </p>
Data for Center-surround interactions underlie bipolar cell motion sensitivity in the mouse retina
<p>Data from the publication "Center-surround interactions underlie bipolar cell motion sensitivity in the mouse retina" published in <em>Nature Communications</em> (2022) https://doi.org/10.1038/s41467-022-32762-7.</p> <p>Code for working with this dataset may be found at https://github.com/eulerlab/bc-motion</p>
Data from: Awake responses suggest inefficient dense coding in the mouse retina
<p><span>The structure and function of the vertebrate retina have been extensively studied across species with an isolated, <em>ex vivo</em> preparation. Retinal function <em>in vivo</em>, however, remains elusive, especially in awake animals. Here we performed single-unit extracellular recordings in the optic tract of head-fixed mice to compare the output of awake, anesthetized, and <em>ex vivo </em>retinas. While the visual response properties were overall similar across conditions, we found that awake retinal output had in general 1) faster kinetics with less variability in the response latencies; 2) a larger dynamic range; and 3) higher firing activity, by ~20 Hz on average, for both baseline and visually evoked responses. Our modeling analyses further showed that such awake response patterns convey comparable total information but less efficiently, and allow for a linear population decoder to perform significantly better than the anesthetized or <em>ex vivo</em> responses. These results highlight distinct retinal behavior in awake states, in particular suggesting that the retina employs dense coding <em>in vivo</em>, rather than sparse efficient coding as has been often assumed from<em> ex vivo</em> studies.</span></p>
Cone bipolar cell synapses generate transient versus sustained signals in parallel ON pathways of the mouse retina
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Data from: Awake responses suggest inefficient dense coding in the mouse retina
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Quantifying the influence of optical coherence tomography beam tilt in the normal adult mouse retina
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Compromised 2-start zigzag chromatin folding in immature mouse retina cells driven by irregularly spaced nucleosomes with short DNA linkers
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Serial block face scanning electron micrographs of mouse outer retina
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Comprehensive single-cell atlas of the mouse retina
<p><strong>Abstract:</strong></p> <p>Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of cellular heterogeneity at the single-cell resolution by classifying and characterizing cell types in multiple tissues and species. While several mouse retinal scRNA-seq reference datasets have been published, each dataset either has a relatively small number of cells or is focused on specific cell classes, and thus is suboptimal for assessing gene expression patterns across all retina types at the same time. To establish a unified and comprehensive reference for the mouse retina, we first generated the largest retinal scRNA-seq dataset to date, comprising approximately 190,000 single cells from C57BL/6J mouse whole retinas. This dataset was generated through the targeted enrichment of rare population cells via antibody-based magnetic cell sorting. By integrating this new dataset with public datasets, we conducted an integrated analysis to construct the Mouse Retina Cell Atlas (MRCA) for wild-type mice, which encompasses over 330,000 single cells. The MRCA characterizes 12 major classes and 138 cell types. It captured consensus cell type characterization from public datasets and identified additional new cell types. To facilitate the public use of the MRCA, we have deposited it in CELLxGENE, UCSC Cell Browser, and the Broad Single Cell Portal for visualization and gene expression exploration. The comprehensive MRCA serves as an easy-to-use, one-stop data resource for the mouse retina communities.</p> <p> </p> <p><strong>Data description:</strong></p> <p>1. MRCA: scRNA-seq of the mouse retina - all cells<br>This file contains the full 330K single cells of the MRCA.<br><br>2. MRCA: scRNA-seq of the mouse retina - bipolar cell subclass<br>This file contains 147K single cells for bipolar cell subcass of the MRCA.</p> <p>3. MRCA: scRNA-seq of the mouse retina - RGC subclass<br>This file contains 77K single cells for retinal ganglion cell subclass of the MRCA.</p> <p>4. MRCA: scRNA-seq of the mouse retina - amacrine cell subclass<br>This file contains 43K single cells for amacrine cell subclass of the MRCA.</p> <p> </p>
Light damage induces inflammatory factors in mouse retina and vitreous humor
<p>Supplemental Files</p>
Influence of amyloid pathology on retina and dLGN in 5xFAD mouse model
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Spaceflight effects on the mouse retina: Histological gene expression and epigenetic changes after flight on STS-135
We report the findings of an animal experiment onboard STS-135 investigating the molecular aspects of the impact of spaceflight on retinal biology by performing differential gene expression profiling between mice flown onboard STS-135 and their ground control counterparts.
Anti YTHDF2 RIP-seq to identify YTHDF2 target mRNAs in P0 mouse retinas
GEO Series GSE145390. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional Heterogeneity and Differential Response of Rod Photoreceptor Pathway Uncovered by Single‐Cell RNA Sequencing of the Aging Mouse Retina
GEO Series GSE230049. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Subtypes of Gbx2+ amacrine cells in mouse retina
GEO Series GSE157271. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome comparison of RhoP23H/+ mouse retina with wildtype at different age
GEO Series GSE281959. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Six3 and Six6 jointly regulate the identities and developmental trajectories of multipotent retinal progenitor cells in the embryonic mouse retina
GEO Series GSE241946. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Retinal ganglion cell-derived semaphorin 6A segregates starburst amacrine cell dendritic scaffolds to organize the mouse inner retina
GEO Series GSE267419. Mus musculus. 855 samples. Type: Expression profiling by high throughput sequencing.
Epigenetic and transcriptional impairments in a retina of SCA7140Q/140Q and SCA7140Q/5Q knock-in mouse model of spinocerebellar ataxia type 7 [RNA-seq]
GEO Series GSE181323. Mus musculus. 7 samples. Type: Expression profiling by high throughput sequencing.
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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.