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Sample GSM4246979

Query DataSets for GSM4246979

Status

Public on Jan 03, 2020

Title

CSP-N721-S516_S221

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

CSP

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