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Sample GSM4021911

Query DataSets for GSM4021911

Status

Public on Aug 27, 2019

Title

Neo_BM_immB_HET_rep4

Sample type

SRA

Source name

Bone marrow immature B cells

Organism

Mus musculus

Characteristics

strain: B6.Cg-Lin28btm1.1Gqda/J
age: 3 day old neonate
genotype: Lin28b heterozygous (HET)
Sex: Not determined
cell type: Bone marrow immature B cells

Extracted molecule

total RNA

Extraction protocol

BM cells from tet-Lin28b or WT mice fed DOX food for 2 weeks; or 3d old neonatal Lin28b wild-type, heterozygous or knockout mice were extracted by crushing the bones from hind limbs, hips, and spine with mortar and pestle. Adult BM cells were subjected to red blood cell lysis, neonatal BM was not subjected to RBC lysis. Total adult BM cells were then pre-enriched by MACS (Miltenyi Biotec) depletion of Lineage+ cells (Ter119+Gr1+CD11b+CD3e+) according to manufacturer’s instructions prior to FACS sorting. Neonatal BM was not pre-enriched before sorting. Antibody staining was performed in FACS buffer (HBSS,supplemented with 0.5% BSA and 2 mM EDTA) at a density of maximum 1x107 cells/100uL volume for 30 min on ice. Immature B cells (CD19+B220loCD93+IgM+CD24hi) were sorted into cold FACS buffer, spun down and resuspended in RNAzol reagent (Sigma-Aldrich). Total RNA was extracted according to the manufacturers instructions. Libraries were generated using the Smartseq V4 Ultra Low input RNA Library Prep Kit (Clontech) and the Nextera XT DNA indexing kit (Illumina) according to the manufacturer’s instructions. Libraries were indexed using the Nextera XT v2 indexing kit (Illumina) according to the manufacturers instructions. Libraries were sequenced on an Illumina Nextseq system using a Nextseq V500/550 150cycle high output kit. Reads were aligned using STAR aligner v2.7.1 (80) and counted using RSEM v.1.28.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina NextSeq 500

Data processing

Paired-end sequenced RNA-seq data was processed as following: RNA-sequenced reads were trimmed TrimeGalore for removal of adapter –and low quality sequences. Resulting reads were then mapped onto the mouse genome build mm10 with STAR (Dobin et al., 2013) and post-processed with RSEM (http://deweylab.github.io/RSEM/) (Li and Dewey, 2011) according to the settings in the ENCODE long-rna-seq-pipeline (https://github.com/ENCODE-DCC/long-rna-seq-pipeline/blob/master/DAC/STAR_RSEM.sh) with the minor modifications that settings “--output-genome-bam --sampling-for-bam” was added to rsem-calculate-expression. STAR and RSEM reference libraries were created from genome build mm10 together with the Ensembl gene model file Mus_musculus.NCBIM37.66.gtf. For analysis of statistical significance among differentially expressed genes the expected gene counts were derived for each RSEM gene result file and catenated to one table which was imported into R using tximport (https://bioconductor.org/packages/release/bioc/html/tximport.html) and analyzed for differential expression using the DESeq2 package ( https://www.bioconductor.org/packages/devel/bioc/html/DESeq2.html) (Love et al., 2014).
Paired-end reads' average insert size and standard deviation determined using bamPEFragmentSize 3.1.3 from the Picard suite on genome coordinate derived bam-file from RSEM v1.2.28.
Genome_build: mm10
Supplementary_files_format_and_content: Expected count matrix generated with rsem

Submission date

Aug 08, 2019

Last update date

Aug 28, 2019

Contact name

Jonas Ungerback

E-mail(s)

[email protected]

Phone

+46733106131

Organization name

Lund University