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| Status |
Public on Mar 11, 2022 |
| Title |
sci-RNA-seq3 with E8.5 mouse embryo PE-09E |
| Sample type |
SRA |
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| Source name |
mouse embryos
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| Organism |
Mus musculus |
| Characteristics |
developmental stage: mouse embryo (E8.5), early somitogenesis
strain: C57BL/6
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| Growth protocol |
For newly generated E8.5b data, C57BL/6 mice were obtained at The Jackson Laboratory. In brief, timed matings of mice were performed via standard husbandry procedures. On the morning of E8.5, individual decidua were removed and placed in ice cold PBS during the harvest. Individual embryos were dissected free of extraembryonic membranes, imaged, and the number of somites present were noted prior to snap freezing in liquid nitrogen. Samples were stored at -80C until further processing.
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| Extracted molecule |
polyA RNA |
| Extraction protocol |
We performed a simplified, optimized version of sci-RNA-seq3 (Cao et al. 2019). Briefly, to each tube, 100ul of a hypotonic, PBS-based lysis buffer was added with DEPC as an RNase inhibitor. The resulting nuclei were then fixed with 4 volumes of a mix of methanol and dithiobis (succinimidyl propionate) (DSP). After rehydrating and washing the nuclei carefully in a sucrose/PBS/triton buffer (SPBST), the nuclei were distributed to a 96-well plate for reverse transcription, allocating 8 wells per embryo. After reverse transcription, nuclei were pooled, washed in SPBST and redistributed to a fresh plate for ligation of the second index primer with T4 DNA ligase. Nuclei were then again pooled, washed, and redistributed to 5 final plates for second strand synthesis, extraction, tagmentation, and PCR to add the third index plus a plate index. Products were pooled by PCR plate, size-selected and sequenced on an Illumina NovaSeq.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Description |
sci-RNA-seq3 with E8.5 mouse embryo
sci-RNA-seq3 library
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| Data processing |
Base calls were converted to fastq format using Illumina’s bcl2fastq/v2.20 and demultiplexed based on PCR i5 and i7 barcodes using maximum likelihood demultiplexing package deML (Renaud et al. 2015) with default settings. Downstream sequence processing and single cell digital expression matrix generation were similar to sci-RNA-seq (Cao et al. 2017) except that RT index was combined with hairpin adaptor index, and thus the mapped reads were split into constituent cellular indices by demultiplexing reads using both the RT index and ligation index (Levenshtein edit distance (ED) < 2, including insertions and deletions).
Briefly, demultiplexed reads were filtered based on RT index and ligation index (ED < 2, including insertions and deletions) and adaptor-clipped using trim_galore/v0.6.5 with default settings. Trimmed reads were mapped to the mouse reference genome (mm10) for mouse embryo nuclei, using STAR/v2.6.1d (Dobin et al. 2013) with default settings and gene annotations (GENCODE VM12 for mouse). Uniquely mapping reads were extracted, and duplicates were removed using the unique molecular identifier (UMI) sequence (ED < 2, including insertions and deletions), reverse transcription (RT) index, hairpin ligation adaptor index and read 2 end-coordinate (i.e. reads with UMI sequence less than 2 edit distance, RT index, ligation adaptor index and tagmentation site were considered duplicates).
Finally, mapped reads were split into constituent cellular indices by further demultiplexing reads using the RT index and ligation hairpin (ED < 2, including insertions and deletions). To generate digital expression matrices, we calculated the number of strand-specific UMIs for each cell mapping to the exonic and intronic regions of each gene with python/v2.7.13 HTseq package (Anders, Pyl, and Huber 2015). For multi-mapped reads, reads were assigned to the closest gene, except in cases where another intersected gene fell within 100 bp to the end of the closest gene, in which case the read was discarded. For most analyses we included both expected-strand intronic and exonic UMIs in per-gene single-cell expression matrices.
Genome_build: mm10
Supplementary_files_format_and_content: Processed data files include a cell annotation csv file, gene annotation csv file, and a gene count sparse matrix file
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| Submission date |
Oct 18, 2021 |
| Last update date |
Mar 11, 2022 |
| Contact name |
Chengxiang Qiu |
| E-mail(s) |
cxqiu@uw.edu
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| Organization name |
University of Washington
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| Department |
Genome Sciences
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| Lab |
Jay Shendure
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| Street address |
William H. Foege Hall, 3720 15th Ave NE
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| City |
Seattle |
| State/province |
WA |
| ZIP/Postal code |
98195 |
| Country |
USA |
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| Platform ID |
GPL24247 |
| Series (2) |
| GSE186069 |
Systematic reconstruction of the cellular trajectories of mammalian embryogenesis (E8.5) |
| GSE186070 |
Systematic reconstruction of the cellular trajectories of mammalian embryogenesis |
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| Relations |
| BioSample |
SAMN22373306 |
| SRA |
SRX12675887 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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