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| Status |
Public on Apr 19, 2021 |
| Title |
Liver_SeqScope_2nd |
| Sample type |
SRA |
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| Source name |
Mouse liver
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| Organism |
Mus musculus |
| Characteristics |
tissue: OCT-frozen liver
condition: Normal and Injured liver tisssues from mice. Normal liver was collected from 8 week-old control (Depdc5F/F/Tsc1F/F, male) mouse. Injured liver was collected from TD (Alb-Cre/Depdc5F/F/Tsc1F/F, female) mouse.
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| Growth protocol |
Standard Mouse rearing condition
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| Extracted molecule |
total RNA |
| Extraction protocol |
Seq-Scope experiment is divided into two consecutive sequencing steps: 1st-Seq and 2nd-Seq. 1st-Seq of Seq-Scope starts with the solid-phase amplification of a single-stranded synthetic oligonucleotide library using an Illumina sequencing-by-synthesis (SBS) platform. 2nd-Seq of Seq-scope begins with overlaying the tissue section slice onto the HDMI-array.
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| Library strategy |
OTHER |
| Library source |
transcriptomic |
| Library selection |
other |
| Instrument model |
HiSeq X Ten |
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| Description |
SeqScope 2nd-Seq library
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| Data processing |
Library strategy: Seq-Scope
Sequencing by Illumina HiSeqX, HiSeq4000 and NovaSeq platforms .
Tissue Boundary Detection: The HiSeq data were joined into MiSeq data according to their HDMI sequence. For each of HiSeq data whose HDMI is found from MiSeq, tile number and XY coordinates were assigned. A density plot was generated to visualize the density of HiSeq reads in a given XY space of each tile. The density plots were manually assigned to the corresponding H&E images. The process is done with customized codes written in Python 3.7.1.
Alignment: From MiSeq data, HDMI sequences of clusters located on the bottom tile were extracted and used as a “whitelist” for the cell (HDMI) barcode. First 9 basepairs of HiSeq data Read 2 were copied to Read 1 and used as the unique molecular identifier (UMI). Read 2 was trimmed at the 3’end to remove polyA tails of length 10 or greater, then aligned to mouse genome (mm10) using GeneFull and Velocyto option with no length threshold and no cell filtering using Star/StarSolo 2.7.5c
Data Binning and Collapsing: The digital expression matrix generated by STARsolo with GeneFull option were combined with spatial information, and further the imaging space were divided into into 100 μm2 (10 μm-sided) square grids and collapsing all HDMI-UMI information into one barcode per grid. Alternatively, data binning was also performed with square 25 μm2 (5 μm-sided) square grids. After data binning, gene types were filtered to only contain protein_coding genes, lncRNA genes, or immunoglobulin/T cell receptor genes, to contain only the first-appearing splicing isoform, and to exclude hypothetical gene models (genes designated as Gm-number).
Clustering: The binned and processed DGE matrix was analyzed in the Seurat v4 package. Feature number threshold was applied to remove the grids that corresponded to the area that was not overlaid by the tissue or was extensively damaged through scratches. Data were normalized using regularized negative binomial regression implemented in Seurat’s SCTransform function. Clustering was performed using the shared nearest neighbor modularity optimization implemented in Seurat’s FindClusters function
Subcellular analysis: Genes from digital expression matrix generated by STARsolo Velocyto option were devided into three groups , and three groups of spliced and unspliced read counts were obtained and then independent images were produced. By plotting spliced and unspliced read counts in each group were compared with each other.
Genome_build: mm10
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| Submission date |
Mar 26, 2021 |
| Last update date |
Apr 21, 2021 |
| Contact name |
Jun Hee Lee |
| E-mail(s) |
leeju@umich.edu
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| Organization name |
University of Michigan
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| Street address |
109 Zina Pitcher Pl
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| City |
Ann Arbor |
| State/province |
MI |
| ZIP/Postal code |
48109-2200 |
| Country |
USA |
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| Platform ID |
GPL21273 |
| Series (1) |
| GSE169706 |
Seq-Scope: Submicrometer-resolution spatial barcoding technology that enables microscopic examination of tissue transcriptome at single cell and subcellular levels |
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| Relations |
| BioSample |
SAMN18509347 |
| SRA |
SRX10457008 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM5212844_Liver_SeqScope_barcode.tsv.gz |
62.6 Mb |
(ftp)(http) |
TSV |
| GSM5212844_Liver_SeqScope_features.tsv.gz |
259.9 Kb |
(ftp)(http) |
TSV |
| GSM5212844_Liver_SeqScope_matrix.mtx.gz |
151.1 Mb |
(ftp)(http) |
MTX |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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