Whole transcriptome data analysis of mouse embryonic hematopoietic stem and progenitor cells that lack Geminin expression

We performed cDNA microarrays (Affymetrix Mouse Gene 1.0 ST Chip) to analyze the transcriptome of hematopoietic stem and progenitor cells (HSPCs) from E15.5dpc wild type and Geminin (Gmnn) knockout embryos. Lineage negative cells from embryonic livers were isolated using fluorescence activated cell sorting. RNA samples were used to examine the transcriptional programs regulated by Geminin during embryonic hematopoiesis. The data sets were analyzed using the GeneSpring v12.5 platform (Agilent). The list of differentially expressed genes was filtered in meta-analyses to investigate the molecular basis of the phenotype observed in the knockout embryos, which exhibited defective hematopoiesis and death. The data from this study are related to the research article “Geminin deletion increases the number of fetal hematopoietic stem cells by affecting the expression of key transcription factors” (Karamitros et al., 2015) [1]. The microarray dataset has been deposited at the Gene Expression Omnibus (GEO) under accession GEO: GSE53056.


a b s t r a c t
We performed cDNA microarrays (Affymetrix Mouse Gene 1.0 ST Chip) to analyze the transcriptome of hematopoietic stem and progenitor cells (HSPCs) from E15.5dpc wild type and Geminin (Gmnn) knockout embryos. Lineage negative cells from embryonic livers were isolated using fluorescence activated cell sorting. RNA samples were used to examine the transcriptional programs regulated by Geminin during embryonic hematopoiesis. The data sets were analyzed using the GeneSpring v12.5 platform (Agilent). The list of differentially expressed genes was filtered in metaanalyses to investigate the molecular basis of the phenotype observed in the knockout embryos, which exhibited defective hematopoiesis and death. The data from this study are related to the research article "Geminin deletion increases the number of fetal hematopoietic stem cells by affecting the expression of key transcription factors" (Karamitros et al., 2015) [1].
The microarray dataset has been deposited at the Gene Expression Omnibus (GEO) under accession GEO

Value of the data
Transcriptomics analysis of embryonic hematopoietic stem and progenitor cells that lack Geminin expression is described.
The present dataset relates to defective hematopoiesis with a differentiation block early in the hematopoietic hierarchy. It is anticipated that similar phenotypes can be interpreted using comparative analyses with our data.
Moreover, the list of differentially expressed genes includes changes in transcription factors and epigenetic regulators that can link Geminin, a cell cycle inhibitor, with novel cellular pathways.
Finally, this dataset can serve as a reference point for various studies pertaining to hematopoietic cell lineage commitment/differentiation and hematopoietic malignancies.

Data
Here we present a qualitative evaluation of microarray data in the format of heatmaps, following hierarchical clustering analysis (Fig. 1). Additionally, we have included a concise set of meta-analyses, both Gene Ontology using DAVID and GSEA (Fig. 2), as well as a listing of the KEGG pathways (Table 1) affected by the differentially expressed genes [4][5][6]. Briefly, the dataset is from whole transcriptome analysis of hematopoietic stem and progenitor cells (HSPCs) isolated from E15.5dpc embryo livers. In this study, control and Geminin knockout littermate embryos were utilized in order to examine the role of Geminin in the developing mouse hematopoietic system. Control were those embryos whose genotype had both Geminin alleles intact, whereas both alleles were disrupted/absent in the Geminin fl/ko Vav1:iCre counterparts in a tissue-specific manner [1,2].
The transcriptome of both groups was examined by means of cDNA microarrays and differentially expressed genes are presented as fold change of knockout versus control expression levels.

RNA extraction
Total RNA was extracted from FACS-sorted cells using the RNeasy MicroKit (Qiagen). RNA integrity was assessed with an Agilent 2000 Bioanalyzer.

Microarray preparation
Samples were enzymatically fragmented and biotinylated using the WT Terminal Labeling Kit (Affymetrix). Samples were hybridized using Affymetrix hybridization kit materials. Washing was done in GeneChip Fluidics Station 450. The chips were scanned using the Affymetrix Scanner 3000 7G with autoloader.

Microarray data analysis
The data were processed and analyzed using GeneSpring (v.12.5, Agilent). Statistical significance was assessed using Student's T-test unpaired (two separate sets of independent and identically distributed samples) with a 95% confidence interval (P-value o0.05). The cutoff value for the fold change of the genes was set to be greater than 1.5. The analysis was carried out using the genotype criterion, but non-averaged for the three biological replicates.