Dataset Information

Whole-transcriptome analysis of endothelial to hematopoietic stem cell transition reveals a requirement for Gpr56 in HSC generation.

ABSTRACT: Hematopoietic stem cells (HSCs) are generated via a natural transdifferentiation process known as endothelial to hematopoietic cell transition (EHT). Because of small numbers of embryonal arterial cells undergoing EHT and the paucity of markers to enrich for hemogenic endothelial cells (ECs [HECs]), the genetic program driving HSC emergence is largely unknown. Here, we use a highly sensitive RNAseq method to examine the whole transcriptome of small numbers of enriched aortic HSCs, HECs, and ECs. Gpr56, a G-coupled protein receptor, is one of the most highly up-regulated of the 530 differentially expressed genes. Also, highly up-regulated are hematopoietic transcription factors, including the "heptad" complex of factors. We show that Gpr56 (mouse and human) is a target of the heptad complex and is required for hematopoietic cluster formation during EHT. Our results identify the processes and regulators involved in EHT and reveal the surprising requirement for Gpr56 in generating the first HSCs.

SUBMITTER: Solaimani Kartalaei P

PROVIDER: S-EPMC4291529 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Whole-transcriptome analysis of endothelial to hematopoietic stem cell transition reveals a requirement for Gpr56 in HSC generation.

Solaimani Kartalaei Parham P Yamada-Inagawa Tomoko T Vink Chris S CS de Pater Emma E van der Linden Reinier R Marks-Bluth Jonathon J van der Sloot Anthon A van den Hout Mirjam M Yokomizo Tomomasa T van Schaick-Solernó M Lucila ML Delwel Ruud R Pimanda John E JE van IJcken Wilfred F J WF Dzierzak Elaine E

The Journal of experimental medicine 20141229 1

Hematopoietic stem cells (HSCs) are generated via a natural transdifferentiation process known as endothelial to hematopoietic cell transition (EHT). Because of small numbers of embryonal arterial cells undergoing EHT and the paucity of markers to enrich for hemogenic endothelial cells (ECs [HECs]), the genetic program driving HSC emergence is largely unknown. Here, we use a highly sensitive RNAseq method to examine the whole transcriptome of small numbers of enriched aortic HSCs, HECs, and ECs. ...[more]

PMID: 25547674

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Project description:During adult bone marrow hematopoiesis, extremely rare and dormant hematopoietic stem cells (HSCs) harbor the highest self-renewal activity within all blood cells. They give rise to active HSCs, which generate multipotent progenitors (MPPs) which differentiate into lineage-committed progenitors and subsequently mature cells. While HSCs are characterized by long-term self-renewal capacity, quiescence and multipotency, MPPs show steadily decreasing self-renewal activity, are cycling but are thought to maintain multipotency. To establish a comprehensive genome-wide landscape of expressed transcripts, we performed a quantitative transcriptome analysis by next-generation sequencing (RNA-seq) of seven ex vivo FACS-sorted mouse HSC/progenitor populations. Eleven-fold coverage of the genome was achieved, revealing quantification of > 27,000 mRNA species of which 589 long non-coding RNAs (lncRNAs) were quantified. A profile of 79 differentially expressed lncRNAs in HSC-MPPs was identified suggesting a role for these RNA species in HSC/progenitor biology. Expression clusters of transcription factors and cell adhesion molecules are identified between the different cell populations. Dormant HSCs, as identified by label-retaining assays, showed a highly differential expression profile compared to active HSCs. In addition to >200 differentially expressed cell surface receptors and lncRNAs, processes including metabolism, development, immune response, signaling (TGFb, Kit, senescence/autophagy) are distinct between the two types of HSCs. In addition, using whole cell proteome analysis of FACS-sorted HSCs and MPP1, >6,000 proteins were identified by quantitative tandem mass spectrometry. Quantification of these proteins confirmed the close relationship between these cell types also seen in their transcript profile and revealed processes such as energy metabolism, immune response and cell cycle to be modulated along early lineage progression. While MPP1/2 still show multilineage potential in reconstitution experiments, a strong lineage bias and low self-renewal potential is observed in mice reconstituted with MPP3/4. These functional differences are accompanied by complex changes in their transcriptome and is also revealed by principal component analysis. In summary, the global mRNA, lncRNA and proteome signatures uncovered here and which are complemented by functional assays, provide a comprehensive and searchable resource of the molecular make-up of the entire HSC/progenitor population present in the bone marrow. These data will provide the basis for a global understanding of stem cell biology in the adult blood system. The uploaded dataset corresponds to the quantitative proteomic comparison of HSC and MPP1, which was done in three biological replicates. Data analysis: MS raw data files were processed with MaxQuant (version 1.3.0.5) (Cox and Mann 2008). Enzyme specificity was set to trypsin/P and a maximum of two missed cleavages were allowed. Cysteine carbamidomethylation and methionine oxidation were selected as fixed and variable modifications, respectively. The derived peak list was searched using the built-in Andromeda search engine (version 1.3.0.5) in MaxQuant against the Uniprot mouse database (2013.02.20) containing 75,721 proteins to which 247 frequently observed contaminants as well as reversed sequences of all entries had been added. Initial maximal allowed mass tolerance was set to 20 ppm for peptide masses, followed by 6 ppm in the main search, and 0.5 Dalton for fragment ion masses. The minimum peptide length was set to six amino acid residues and three labeled amino acid residues were allowed. A 1% false discovery rate (FDR) was required at both the protein level and the peptide level. In addition to the FDR threshold, proteins were considered identified if they had at least one unique peptide. The protein identification was reported as an indistinguishable “protein group” if no unique peptide sequence to a single database entry was identified. The ‘match between runs’ was enabled for consecutive peptide fractions with a 2 minutes time window. The iBAQ algorithm was used for estimation of the abundance of different proteins within a single sample (proteome) (Schwanhausser 2011). For evaluation of differential protein expression between HSC and MPP1, statistical analysis was performed for the proteins quantified in all three replicates using the Limma package in R/Bioconductor (Gentleman 2004, Smyth 2004). After fitting a linear model to the data, an empirical Bayes moderated t-test was used for the protein ratios, which were weighted on log10(summed peptide intensities) in order to capture the effect that the statistical spread of unregulated proteins is much more focused for highly abundant proteins than for low abundance ones (Cox 2008). P-values were then adjusted for multiple testing with Benjamini and Hochberg's method and proteins with an adjusted p-value lower than 0.1 were considered to be differentially expressed between HSC and MPP1. Associated transcriptomics data has been deposited at ArrayExpress with accession E-MTAB-2262.

Dataset Information

Whole-transcriptome analysis of endothelial to hematopoietic stem cell transition reveals a requirement for Gpr56 in HSC generation.

Publications

Whole-transcriptome analysis of endothelial to hematopoietic stem cell transition reveals a requirement for Gpr56 in HSC generation.

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