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GEO help: Mouse over screen elements for information. |
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| Status |
Public on Jan 03, 2020 |
| Title |
6C3-N712-S508_S166 |
| Sample type |
SRA |
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| Source name |
Long Bones
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| Organism |
Mus musculus |
| Characteristics |
strain: BL6
tissue: Bone and Bone marrow
age: Post-natal day 3 (P3)
gating strategy: CD45-Ter-119-AlphaV+Thy-6C3+CD105+
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| Extracted molecule |
total RNA |
| Extraction protocol |
We sorted live individual skeletal stem and progenitor populations (mSSC, CSP, Thy+, and 6C3+) by double sorting on FACS ARIA 2. Sorted cells were captured on a small-sized (5–10 μm cell diameter) microfluidic RNA-seq chip (Fluidigm, South San Francisco, CA, USA) using the Fluidigm C1 system. We loaded 10 μl of 500–1000 cells/μl onto the chip and imaged each capture site after the capture run to assess the number and viability of cells by phase-contrast and fluorescence microscopy. We included only single, live cells in the analysis.
We prepared amplified cDNAs on chip using C1 mRNA-RT+Amp program that uses reagents from the SMARTer Ultra Low RNA kit for Illumina (Clontech, Takara Bio Group, Mountain View, CA, USA) as per protocol provided by Fluidigm. We added the ERCC (External RNA Controls Consortium) RNA spike-in Mix (Ambion, Life Technologies, NY, USA) to the lysis reaction to be processed in parallel to cellular messenger RNA. For each C1 experiment, we processed a bulk RNA control (about 200 cells) and a no-cell negative control in parallel in PCR tubes, using the same reagent mixes as used on chip. We constructed libraries from the diluted cDNAs in 96-well plates using the Nextera XT DNA Sample Preparation kit (Illumina, San Diego, CA, USA) as described previously (Treutlein et al., 2014) using the protocol supplied by Fluidigm (Fluidigm). We quantified the libraries by Agilent Bioanalyzer, using High Sensitivity DNA analysis kit, and also fluorometrically, using Qubit dsDNA HS Assay kits and a Qubit 2.0 Fluorome
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
6C3+
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| Data processing |
Raw reads were preprocessed with the sequence-grooming tools FASTQC30 (Treutlein et al., 2014) cutadapt31 (Treutlein et al., 2014) and PRINSEQ32 (Treutlein et al., 2014).
We mapped the processed reads with Olego (Wu et al., 2013) (http://nar.oxfordjournals.org/content/41/10/5149) and used SAMtools (Li et al., 2009) (http://www.ncbi.nlm.nih.gov/pubmed/19505943) for processing of post-map ∗.sam files generated by Olego.
We quantified the transcript levels as fragments per kilobase of transcript per million mapped reads (FPKM) generated by Cuffdiff2 (Trapnell et al., 2013) (http://www.nature.com/nbt/journal/v31/n1/full/nbt.2450.html) using the default geometrical scaling and blind dispersion model options.
We applied stringent filter criteria as described before (Treutlein et al., 2014) to weed out cells with suboptimal data, which may result from unhealthy cells or other technical reasons.
Genome_build: mm10
Supplementary_files_format_and_content: Tab-delimited text file containing a FPKM-normalized gene expression table
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| Submission date |
Jan 02, 2020 |
| Last update date |
Jan 03, 2020 |
| Contact name |
Charles Chan KF |
| E-mail(s) |
chazchan@gmail.com
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| Organization name |
Stanford
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| Street address |
265 Campus Drive
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| City |
Stanford |
| State/province |
CA |
| ZIP/Postal code |
94305-5461 |
| Country |
USA |
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| Platform ID |
GPL19057 |
| Series (2) |
| GSE64447 |
Neonatal Skeletal Progenitors |
| GSE142873 |
Identification and specification of the mouse skeletal stem cell. |
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| Relations |
| BioSample |
SAMN13714722 |
| SRA |
SRX7494341 |
| 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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