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Sample GSM4247075 Query DataSets for GSM4247075
Status Public on Jan 03, 2020
Title THY-N724-S505_S32
Sample type SRA
 
Source name Long Bones
Organism Mus musculus
Characteristics strain: BL6
tissue: Bone and Bone marrow
age: Post-natal day 3 (P3)
gating strategy: CD45-Ter-119-Tie2-AlphaV+Thy+6C3-CD105+
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
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina NextSeq 500
 
Description THY+
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
 
Submission date Jan 02, 2020
Last update date Jan 03, 2020
Contact name Charles Chan KF
E-mail(s) chazchan@gmail.com
Organization name Stanford
Street address 265 Campus Drive
City Stanford
State/province CA
ZIP/Postal code 94305-5461
Country USA
 
Platform ID GPL19057
Series (2)
GSE64447 Neonatal Skeletal Progenitors
GSE142873 Identification and specification of the mouse skeletal stem cell.
Relations
BioSample SAMN13714596
SRA SRX7494465

Supplementary data files not provided
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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