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SRX6889720: GSM4090628: RGC061616p9_B10_S214; Mus musculus; RNA-Seq
1 ILLUMINA (NextSeq 500) run: 2.2M spots, 160.9M bases, 62.8Mb downloads

Submitted by: NCBI (GEO)
Study: Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes - Atlas of adult mouse retinal ganglion cells [Smart-seq2]
show Abstracthide Abstract
Neuronal types in the central nervous system differ dramatically in their resilience to injury or insults. Here we studied selective resilience in mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ~80% of RGCs in 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 45 RGC types in adult retina. We tracked their survival after ONC, characterized transcriptomic, morphological, and physiological changes that preceded degeneration, and identified genes selectively expressed by each type. Finally, loss- and gain-of-function assays in vivo showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury, and demonstrates that these responses can be used to reveal molecular targets for intervention. Overall design: In this experiment, we FAC sorted for GFP expressing cells in the W3-GFP mouse line that were also positive for the retinal ganglion cell surface protein CD90 from dissociated cells from retinas of postnatal day 15 mice
Sample: RGC061616p9_B10_S214
SAMN12821960 • SRS5422689 • All experiments • All runs
Organism: Mus musculus
Library:
Instrument: NextSeq 500
Strategy: RNA-Seq
Source: TRANSCRIPTOMIC
Selection: cDNA
Layout: PAIRED
Construction protocol: Retinas were dissected in oxygenated AMES, digested in papain, and dissociated to single cell suspensions using manual trituration in ovomucoid solution.  Single cell suspensions were incubated with 0.5ul of anti-CD90 (conjugated to various fluorophores) (Thermo Fisher Scientific) for 10 million cells per 100µl. Cells were sorted using a MoFlo Astrios. Cellular debris, doublets, and dead cells were excluded, and RGCs were collected based on high Cd90 and GFP co-expression.  Singe cells were sorted into 2ul lysis buffer per well in multiple 96 well plates, spun down for 1min and immediated placed on dry ice, then stored at -80oC until subsequent processing for Smartseq2 We generated single cell RNA-Seq libraries using a modified Smart-seq2 method [Picelli et al., 2013, Ding et al., 2019] with the following minor change. We added 3 µl instead of 4 µl of master mix containing only 1.7 µl instead of 2.7 µl of 1 M Trehalose (Sigma-Aldrich) directly to the 2 µl cell lysate without a SPRI bead cleanup step. Smart-seq2 per Picelli et al., 2013 with minor modifications (see above)
Experiment attributes:
GEO Accession: GSM4090628
Links:
Runs: 1 run, 2.2M spots, 160.9M bases, 62.8Mb
Run# of Spots# of BasesSizePublished
SRR101644942,171,091160.9M62.8Mb2019-12-01

ID:
9067064

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