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Sample GSM4191792 Query DataSets for GSM4191792
Status Public on Nov 26, 2019
Title WT1
Sample type SRA
Source name Neural progenitor cells
Organism Mus musculus
Characteristics cell type: Neuroephitelial cells
strain: C57BL/6J
genotype: WT
age: E 12.5
Growth protocol Mouse dorsal telencephalon was dissected from E12.5 brains in DMEM/F12 medium (Invitrogen). Cell suspension was obtained by mechanical dissociation. NPCs from each telencephalon were grown individually as neurospheres in 6 well plates and in DMEM/F12 medium supplemented with 1xN2 and 0.5xB27, 10 ng/ml FGF (Invitrogen), 10 μg/ml Insulin and 10 ng/ml bFGF (Sigma Aldrich). Two days after the culture start, wild type (WTNPCs) or Mcph1 KO (KONPCs) primary cultures were pooled by two or three in a T75 flask for further expansion during two to three days. At this stage, neurospheres were pelleted for protein extraction or RNA extraction, or mechanically dissociated for seeding on gelatin-coated dishes, glass coverslips in 24-well plates or IBIDI slides (IBIDI). Attached cells were cultured in DMEM medium (Invitrogen) containing 10% fetal bovine serum, and containing either i) 4,5 g/L Glucose, 1mM sodium pyruvate and 1mM Glutamine (GPGln complete medium); ii) 2mM sodium pyruvate and 1mM Glutamine (PGln medium); iii) 1mM Glutamine only (Gln medium). Cells were then maintained in culture for four days.
Extracted molecule total RNA
Extraction protocol Total RNA was extracted from WTNPCs and WTNPCs. Sample quality and quantification were assessed on Experion chips (Bio-Rad). Twin samples were pooled according to genotype and matching amounts.
Library preparation and Illumina sequencing were performed on wild type and Mcph1 KO samples, two of each, at the Genomic Platform of the Ecole Normale Superieure (Paris, France). Ribosomal RNA depletion was performed with the Ribo-Zero kit (Epicentre), using 1.5 μg of total RNA. Libraries were prepared using the strand specific RNA-Seq library preparation ScriptSeq V2 kit (Epicentre). Libraries were multiplexed by 4 on 1 flow cell lane. A 75bp read sequencing was performed on a HiSeq 1500 device (Illumina). A mean of 39.3 ± 7 million passing Illumina quality filter reads was obtained for each of the 4 samples.
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina HiSeq 1500
Data processing RNA-Seq data analysis was performed by GenoSplice technology ( Sequencing, data quality, reads repartition (e.g., for potential ribosomal contamination), and insert size estimation were performed using FastQC (v0.10.1), Picard-Tools (v1.119), Samtools (v0.1.19) and rseqc (v2.4). Reads were mapped using STAR (v2.3.0) (Dobin et al., 2013).
Gene expression was estimated using Mouse FAST DB v2013_1 annotations. Genes were considered as expressed if their rpkm value was greater than 97.5% of the background rpkm value based on intergenic regions. Raw count data normalization and differential expression analysis were then performed using Deseq (v1.12.1). Results were considered statistically significant for unadjusted p-values ≤ 0.05 and fold-changes ≥ 1.5.
The mouse dataset was annotated with human Ensembl gene ID using BiomaRt Bioconductor R package (Naro et al., 2017; Noli et al., 2015) and selecting human genes that were ‘one-to-one’ orthologues with mouse genes. As previously described (Delahaye-Duriez et al., 2016), we generated a gene-level score reflecting the significance and the intensity of differential expression (multiplying the –log10 of p value by the log-transformed fold change). This score was used as a metric to ‘rank’ genes to test using Gene set enrichment analysis (GSEA) if gene sets defined in the Molecular Signatures database (MSigDB v5.2) occupy higher (or lower) positions in the ranked gene list than what it would be expected by chance (Subramanian et al., 2005). The enrichment was tested for several sets of genes of the MSigDB: Gene ontology (GO) biological process, cellular component and molecular functions, Reactome pathways, and Hallmark gene sets. The MSigDB hallmark gene sets is a collection of 50 gene sets that provide coherently expressed signatures derived by aggregating many MSigDB gene sets (Molecular Signatures Database v5.2) to represent well-defined biological states or processes (Liberzon et al., 2015). Gene set enrichment scores (NES, p value, FDR and FWER) were provided in the GSEA output format developed by Broad Institute of MIT and Harvard (permutations = 10,000).
Supplementary_files_format_and_content: normalized counts
Submission date Nov 25, 2019
Last update date Nov 27, 2019
Contact name Javier Gilabert-Juan
Phone 0033768805677
Organization name College de France
Department CIRB
Street address 11, Marcelin Berthelot
City Paris
ZIP/Postal code 75321
Country France
Platform ID GPL18480
Series (1)
GSE140976 Mcph1 inactivation affected cell cycle progression and survival of neocortical progenitors at the molecular level
BioSample SAMN13384189
SRA SRX7213831

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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