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| Status |
Public on Apr 23, 2024 |
| Title |
Mouse_embryonic_brain_Apcdd1+/-_1 |
| Sample type |
SRA |
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| Source name |
embryonic brain
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| Organism |
Mus musculus |
| Characteristics |
genotype: Apcdd1+/-
tissue: embryonic brain
age: E10.5
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| Extracted molecule |
polyA RNA |
| Extraction protocol |
The E10.5 mouse embryos were dissected from pregnant mice sacrificed by anesthesia and decapitation. The head part of embryo was dissected out by fine tweezers and stored in Shbio®Tissue Preservation Solution (21903-10) overnight, which were then dissociated using Shbio®Tissue Dissociation Kit (219517-10).
Briefly, tissues were incubated in 1 ml enzyme mix on a metal rotor at 37 °C for 15 min, during which specimens were gently mixed for 20 times using 1,000-ml tips every 7 min. Cell dissociations were terminated by adding 2 ml of complete medium and then suspensions were filtered through a 100-µm strainer and centrifuged for 10 min at 500g. The supernatant was discarded and the cell pellet was resuspended with 300 µl suspension buffer (1X DPBS containing 2% FBS). Dyed by 50 ng/ml DAPI for 3 min and refiltered with a 40-µm strainer, cell suspensions were then sorted with FACS BD Aria III sorter to remove dead cells, fragments and lumps. Cell numbers of suspensions were measured with fluorescence cell counter (Luna-FLTM, Logos biosystems) and hemocytometer using trypan blue staining. Cell suspensions were then adjusted to a proper cell concentration for library construction of scRNA-seq. scRNA-seq was then performed using the DNBelab C high throughput single cell RNA library prep kit (MGI) following the manufacturer’s protocol. The QubitTM Flex Fluorometer (Thermo Fisher Scientific) and Agilent Fragment Analyzer were used to determine the concentration and assess the quality of the libraries, which were then subjected to MGISEQ-2000 for sequencing. Cell barcode and unique molecular identifiers (UMI) sequences were parsed using DNBelab_C_Series_HT_scRNA-analysis-software (https://github.com/MGI-tech-bioinformatics/DNBelab_C_Series_HT_scRNA-analysis-software)
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic single cell |
| Library selection |
cDNA |
| Instrument model |
DNBSEQ-G400 |
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| Data processing |
Scanpy (version: 1.9.1)74 was used for downstream analyses. Low-quality cells were filtered out considering the abnormal gene count and high mitochondrial read percentage.
We normalized the gene expression by scaling total UMIs to 10,000 in each cell followed by log transformation.
The BBKNN algorithm was used to remove batch effects across four samples.
Then, principal component analysis (PCA) was performed and the top 50 principal components (PCs) were used for uniform manifold approximation and projection (UMAP) and Leiden clustering.
Because of the different file format of MGI and 10X, some cell IDs in our original barcodes file can be matched with more than one barcodes, which is also the reason for more lines than provided in matrix file.
Assembly: mm10
Supplementary files format and content: barcodes, features, and matrix files
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| Submission date |
Dec 30, 2022 |
| Last update date |
Apr 23, 2024 |
| Contact name |
Ying Liu |
| E-mail(s) |
ying.liu@pku.edu.cn
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| Organization name |
Peking University
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| Department |
College of Future Technology
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| Lab |
Laboratory of Mitochondrial and Metabolism Research
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| Street address |
5 Summer Palace Road, Haidian District, Beijing
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| City |
Beijing |
| ZIP/Postal code |
100871 |
| Country |
China |
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| Platform ID |
GPL28457 |
| Series (1) |
| GSE221928 |
Adaptive Structural Variants Contributing to Human Brain Development Revealed by 1,026 Rhesus Macaque Genomes |
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| Relations |
| BioSample |
SAMN32510419 |
| SRA |
SRX18895041 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM6910169_36_3_barcodes_seq.tsv.gz |
54.3 Kb |
(ftp)(http) |
TSV |
| GSM6910169_36_3_features.tsv.gz |
68.7 Kb |
(ftp)(http) |
TSV |
| GSM6910169_36_3_matrix.mtx.gz |
76.6 Mb |
(ftp)(http) |
MTX |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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