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GEO help: Mouse over screen elements for information. |
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| Status |
Public on Apr 17, 2024 |
| Title |
Setd7 KO Kidney - Control 562 |
| Sample type |
SRA |
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| Source name |
Apoe-/- Setd7 -/-_control_kidney
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| Organism |
Mus musculus |
| Characteristics |
strain background: C57BL/6
genotype/variation: Apoe-/- Setd7 -/-
condition: control
tissue: Kidney
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| Extracted molecule |
total RNA |
| Extraction protocol |
Drop-Seq. Kidney cortex was dissected and homogenized by pressing though a 100uM sieve and glomerular fraction collected using 70uM sieve. Glomerular fraction was dissociated using cold active protease (subtilisin A, Sigma). Single cell RNA was captured using the drop-seq method (Macosko 2015)
Drop-Seq. Sequencing libraries were created from barcoded cDNA (Drop-seq) using the illumina Nextera XT library prep kit (Illumina) as adapted in the Drop-Seq protcol (Macosko 2015)
RNA-Seq. Kidneys were homogenized TRIzol solution. RNA was extracted using the Directzol RNA mini-prep kit according to the manufacturer’s protocol, with DNase I treatment in the column to remove genomic DNA contamination (Zymo Research, Irvine, CA, USA). RNA was eluted in 30 μl TE buffer, and the quantity and quality of RNA examined on a MultiNA bioanalyzer (Shimadzu, Tokyo, Japan).
RNA-Seq. A NEBNext® Poly(A) mRNA Magnetic Isolation Module (New England Biolabs, Ipswich, MA) was used to enrich mRNA from 1 μg of total RNA. The NEBNext® UltraTM Directional RNA Library Prep Kit for Illumina® was then used to generate barcoded libraries according to the manufacturer’s protocol, and these libraries were then quantified on the MultiNA bioanalyzer and pooled to equimolar ratios for sequencing.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 4000 |
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| Data processing |
library strategy: DROP-seq
Drop-Seq:
The primary sequence data was generated using the Illumina bcl2fastq 1.8 pipeline.
Fastq files were processed into a count matrix using Drop-seq tools v2.1, retain top 3000 cell barcodes
RNA-Seq:
The primary sequence data was generated using the Illumina bcl2fastq 1.8 pipeline.
Low-quality bases (Q score < 10) were removed from the 3 end with Skewer 0.2.2 (Jiang et al., 2014)
Mouse genome cDNA sequences were retrieved from Ensembl version 96 (Cunningham et al., 2019). Reads were mapped to transcripts using Kallisto v0.45.0 (Bray et al., 2016). Transcript counts were aggregated to gene-level counts with the sum function in R. Genes with an average of fewer than 10 reads per sample were omitted from downstream analysis
Genome_build: GRCm38
Supplementary_files_format_and_content: RNA-seq gene level count matrix; Single Cell count matrix (gene ~ cell-barcode)
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| Submission date |
Sep 27, 2020 |
| Last update date |
Apr 18, 2024 |
| Contact name |
Assam El-Osta |
| Organization name |
Baker Heart and Diabetes Institute
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| Lab |
Human Epigenetics
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| Street address |
75 Commercial Road
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| City |
Melbourne |
| ZIP/Postal code |
3004 |
| Country |
Australia |
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| Platform ID |
GPL21103 |
| Series (1) |
| GSE158626 |
Targeting Set7 in an experimental model of diabetic nephropathy |
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| Relations |
| BioSample |
SAMN16276581 |
| SRA |
SRX9199915 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM4804555_SET7KC562_DGE.mx.txt.gz |
5.8 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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