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Sample GSM5624602

Query DataSets for GSM5624602

Status

Public on Feb 16, 2022

Title

KO_MSC_AML_REP3

Sample type

SRA

Source name

Bone Marrow

Organism

Mus musculus

Characteristics

strain: C57BL/6J
tissue: Bone Marrow
age: 10-14 weeks
genotype: Lama4-/-
cell type: MLL-AF9 AML Cells
cell subtype: bone marrow Lineage-KIT+ cells were retrovirally transduced with human MLL-AF9 gene

Growth protocol

Lama4-/- MSC or WT MSC were plated onto 12-well plate at 30,000/well, 24h before seeding culture-expanded MLL-AF9 AML cells at 30,000/well. 48h post co-culture, cells from the co-cultures were dissociated by trypsin and MSC (CD45-CD44-Sca1+) and MLL-AF9 cells (CD45.1+) were isolated into RLT buffer via FACs-sorting.

Extracted molecule

total RNA

Extraction protocol

FACS-sorted MSC or MLL-AF9 cells from co-culture system were used for RNA extraction using RNeasy Microkit (Qiagen, USA) according to the manufacturer’s recommendations. cDNA was prepared using SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara Bio. Cat. No. 634898). The cDNA quality was examined on
cDNA was prepared using SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara Bio. Cat. No. 634898).
The cDNA quality was examined on Agilent TapeStation system using a High Sensitivity D5000 ScreenTape (Agilent, Cat. No. 5067-5592). One ng cDNA was used for library preparation using Nextera XT DNA Library Preparation Kit (Illumina, Cat. Nos. FC-131-1024 & FC-131-1096). ). The yield and quality of the amplified libraries were analyzed using Qubit by Thermo Fisher and the Agilent Tapestation System. The indexed cDNA libraries were sequenced on the Illumina 2000 or Nextseq 550 (Illumina, San Diego, CA). for a 75-cycle v2 sequencing run generating 75 bp single-end reads.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

NextSeq 2000

Description

15_KO_MSC_AML9_S15

Data processing

The data were geenerated on Illumina Nextseq 2000 via a 100-cycle p2 sequencing run
Sample quality was assessed using FastQC (v0.11.8) and MultiQC (v1.7). Reads were aligned to a reference built from Ensembl GRCm38 genome sequences using STAR (v2.6.1d).
All mapped counts to each gene were further calculated by FeatureCounts function from Subread package 5 installed in R. Genes with Reads Per Kilobase of transcript per Million mapped reads (RPKM) values more than 0.1 were considered as being actively transcribed and proceeded to the analysis of Differential Gene Expression (DGE).6
The normalized read counts assigned to each sample were generated by Deseq2 and used for unsupervised clustering.
The differentially expressed genes between the MSC subsets were identified by adjusted P value (padj < 0.05) using Benjamini-Hochberg correction for multiple testing, together with thresholds at log2fold changes >1 (up-regulated) or <-1 (down-regulated).
Genome_build: mm10
Supplementary_files_format_and_content: excel file; Matrix table with raw and normarized gene counts for every gene and every sample, together with multiple testing results with Benjamini-Hochberg correction

Submission date

Oct 13, 2021

Last update date

Feb 16, 2022

Contact name

Hong Qian

E-mail(s)

hong.qian@ki.se

Organization name

Karolinska Institute

Department

Department of Medicine