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| Status |
Public on Jul 12, 2021 |
| Title |
Mouse LGN snRNAseq 0 -8 hour stim rep 1-4 (12 samples) |
| Sample type |
SRA |
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| Source name |
C57BL/6J
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| Organism |
Mus musculus |
| Characteristics |
age: P27
treatment: dark-reared
time post-light stim: 0 - 8 h
replicate: 1 to 4
sample type: mixed
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| Extracted molecule |
total RNA |
| Extraction protocol |
Mice were euthanized following dark-rearing between P20 and P27 then re-exposure to light for 0, 1, or 8 hours. The LGNs from 3-4 mice of each condition were pooled to represent one bioreplicate, and four bioreplicates were included in the analysis. After isoflurane anesthetization, mice were decapitated and the brain was isolated. Mouse brains were dissected and 300 um coronal sections were made on a Leica VT1000S vibratome. The dorsal LGNs were then microdissected in ice cold PBS after visual identification using a Nikon SMZ-10A brightfield dissection microscope, and flash frozen.
Individual cells were captured and barcoded using the inDrops platform as previously described. Briefly, single-cell suspensions were fed into a microfluidic device that packaged the cells with barcoded hydrogel microspheres and reverse transcriptase/lysis reagents. After cell encapsulation, primers were photo-released by UV exposure. Two libraries of approximately 3000 cells each were collected for each sample. Indexed libraries were pooled and sequenced on a Nextseq 500 (Illumina).
single-nucleus RNA-sequencing
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
see README_snRNAseq.pdf for sample barcodes
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| Data processing |
Transcripts were processed according to the pipeline in Macosko et al. (2015). Briefly, this pipeline was used to build a custom transcriptome from Ensembl GRCm38 genome and GRCm38.84 annotation using Bowtie 1.1.1, after filtering the annoatation gtf file (gencode.v17.annotation.gtf filtered for feature_type=îgeneî, gene_type="protein_coding" and gene_status="KNOWN"). Read quality control and mapping against this transcriptome was performed. Unique molecular identifiers (UMIs) were used to link sequence reads back to individual captured molecules. All steps of the pipeline were run using default parameters unless explicitly stated.
All cells were combined into a single dataset. Nuclei with >10% mitochondrial content were excluded from the dataset. Cells with fewer than 500 or more than 15,000 UMI counts were excluded. Cells were then clustered using the Seurat R package (Satija et al., 2015). The data were log normalized and scaled to 10,000 transcripts per cell. Variable genes were identified using the following parameters: x.low.cutoff = 0.0125, x.high.cutoff = 3, y.cutoff = 0.5. We limited the analysis to the top 30 principal components (PCs). Clustering resolution was set to 0.6. Clusters containing fewer than 100 cells were discarded. The expression of known marker genes was used to assign each cluster to one of the main cell types. Snap25, Olig1, Aqp4, Cx3cr1, Cldn5, and Vtn were used to identify neurons, oligodendrocytes, astrocytes, microglia, endothelial cells, and pericytes, respectively. Slc17a6 and Gad1 were used to distinguish excitatory and inhibitory neurons, respectively, which comprised the majority of cells analyzed. Clusters with significant expression of two or more markers were removed, as they likely represented doublet clusters resulting from simultaneous capture of two or more nuclei in a single droplet. In total, the final dataset included 8,398 excitatory neurons and 4,987 inhibitory neurons.
Genome_build: Custom transcriptome from Ensembl GRCm38 genome and GRCm38.84 annotation using Bowtie 1.1.1
Supplementary_files_format_and_content: The tsv files are tables showing transcript counts per cell for every gene.
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| Submission date |
Jul 12, 2018 |
| Last update date |
Jul 12, 2021 |
| Contact name |
Lucas Martin Cheadle |
| E-mail(s) |
lucas_cheadle@hms.harvard.edu
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| Organization name |
Harvard Medical School
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| Department |
Neurobiology
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| Lab |
Greenberg
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| Street address |
220 Longwood Ave; Goldenson Bldg 413
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| City |
Boston |
| State/province |
MA |
| ZIP/Postal code |
02115 |
| Country |
USA |
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| Platform ID |
GPL19057 |
| Series (2) |
| GSE117020 |
Visual experience-dependent expression of Fn14 is required for retinogeniculate refinement (stimulus single nucleus RNA-Seq) |
| GSE117024 |
Visual experience-dependent expression of Fn14 is required for retinogeniculate refinement |
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| Relations |
| BioSample |
SAMN09651220 |
| SRA |
SRX4385947 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM3267399_LC_LGN_snRNAseq_Stim_0hr_rep1_counts.tsv.gz |
3.6 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_0hr_rep2_counts.tsv.gz |
3.7 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_0hr_rep3_counts.tsv.gz |
2.7 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_0hr_rep4_counts.tsv.gz |
3.0 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_1hr_rep1_counts.tsv.gz |
4.6 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_1hr_rep2_counts.tsv.gz |
4.4 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_1hr_rep3_counts.tsv.gz |
4.6 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_1hr_rep4_counts.tsv.gz |
3.6 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_8hr_rep1_counts.tsv.gz |
3.4 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_8hr_rep2_counts.tsv.gz |
3.5 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_8hr_rep3_counts.tsv.gz |
3.3 Mb |
(ftp)(http) |
TSV |
| GSM3267399_LC_LGN_snRNAseq_Stim_8hr_rep4_counts.tsv.gz |
3.9 Mb |
(ftp)(http) |
TSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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