The major cell populations of the mouse retina.
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TLDR
With the exception of the monkey fovea, the inner nuclear layers of the three species contain populations of cells that are, overall, quite similar, which contradicts the previous belief that the retinas of lower mammals are “amacrine-dominated”, and therefore more complex, than those of higher mammals.Abstract:
We report a quantitative analysis of the major populations of cells present in the retina of the C57 mouse. Rod and cone photoreceptors were counted using differential interference contrast microscopy in retinal whole mounts. Horizontal, bipolar, amacrine, and Muller cells were identified in serial section electron micrographs assembled into serial montages. Ganglion cells and displaced amacrine cells were counted by subtracting the number of axons in the optic nerve, learned from electron microscopy, from the total neurons of the ganglion cell layer. The results provide a base of reference for future work on genetically altered animals and put into perspective certain recent studies. Comparable data are now available for the retinas of the rabbit and the monkey. With the exception of the monkey fovea, the inner nuclear layers of the three species contain populations of cells that are, overall, quite similar. This contradicts the previous belief that the retinas of lower mammals are “amacrine-dominated”, and therefore more complex, than those of higher mammals.read more
Citations
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Journal ArticleDOI
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
Evan Z. Macosko,Evan Z. Macosko,Anindita Basu,Anindita Basu,Rahul Satija,Rahul Satija,James Nemesh,James Nemesh,Karthik Shekhar,Melissa Goldman,Melissa Goldman,Itay Tirosh,Allison R. Bialas,Nolan Kamitaki,Nolan Kamitaki,Emily M. Martersteck,John J. Trombetta,David A. Weitz,Joshua R. Sanes,Alex K. Shalek,Alex K. Shalek,Alex K. Shalek,Aviv Regev,Aviv Regev,Aviv Regev,Steven A. McCarroll,Steven A. McCarroll +26 more
TL;DR: Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together.
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
Evan Z. Macosko,Evan Z. Macosko,Anindita Basu,Anindita Basu,Rahul Satija,Rahul Satija,James Nemesh,James Nemesh,Karthik Shekhar,Melissa Goldman,Melissa Goldman,Itay Tirosh,Allison R. Bialas,Nolan Kamitaki,Nolan Kamitaki,Emily M. Martersteck,John J. Trombetta,David A. Weitz,Joshua R. Sanes,Alex K. Shalek,Alex K. Shalek,Alex K. Shalek,Aviv Regev,Aviv Regev,Aviv Regev,Steven A. McCarroll,Steven A. McCarroll +26 more
TL;DR: Drop-seq as discussed by the authors analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin, and identifies 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes.
Journal ArticleDOI
SCENIC: single-cell regulatory network inference and clustering.
Sara Aibar,Carmen Bravo González-Blas,Thomas Moerman,Vân Anh Huynh-Thu,Hana Imrichova,Gert Hulselmans,Florian Rambow,Jean-Christophe Marine,Pierre Geurts,Jan Aerts,Joost van den Oord,Zeynep Kalender Atak,Jasper Wouters,Stein Aerts +13 more
TL;DR: On a compendium of single-cell data from tumors and brain, it is demonstrated that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states.
Journal ArticleDOI
The fundamental plan of the retina
TL;DR: The fundamental structural principles of the retina give a bottom-up view of the strategies used in the retina's processing of visual information and suggest new questions for physiological experiments and modeling.
Posted ContentDOI
SCENIC: Single-Cell Regulatory Network Inference And Clustering
Sara Aibar,Carmen Bravo González-Blas,Thomas Moerman,Jasper Wouters,Vân Anh Huynh-Thu,Hana Imrichova,Zeynep Kalender Atak,Gert Hulselmans,Michael Dewaele,Florian Rambow,Pierre Geurts,Jan Aerts,Jean-Christophe Marine,Joost van den Oord,Stein Aerts +14 more
TL;DR: SCENIC (Single Cell rEgulatory Network Inference and Clustering) is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs.
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