Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptional landscape, long non-coding RNAs and post-transcriptional regulation in hematopoietic stem/progenitor cell differentiation

ABSTRACT: Hematopoietic stem cells (HSC) possess life-long self-renewal activity and generate a series of multipotent progenitors that differentiate into lineage-committed progenitors and subsequently mature cells. Recently, functionally distinct stem and progenitor cell types have been identified, however, a systems-wide understanding of the underlying gene regulation is lacking. Here, we present the global transcriptome of ex vivo isolated mouse multipotent hematopoietic stem/progenitor cells (HSPCs, LinnegSca-1+c-Kit+) and myeloid committed precursors (LinnegSca-1-c-Kit+) as revealed by next-generation sequencing (RNA-seq).

INSTRUMENT(S): Illumina HiSeq 2000

ORGANISM(S): Mus musculus

SUBMITTER: Alejandro Reyes

PROVIDER: E-MTAB-1963 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptome-wide profiling and posttranscriptional analysis of hematopoietic stem/progenitor cell differentiation toward myeloid commitment.

Klimmeck Daniel D Cabezas-Wallscheid Nina N Reyes Alejandro A von Paleske Lisa L Renders Simon S Hansson Jenny J Krijgsveld Jeroen J Huber Wolfgang W Trumpp Andreas A

Stem cell reports 20140925 5

Hematopoietic stem cells possess lifelong self-renewal activity and generate multipotent progenitors that differentiate into lineage-committed and subsequently mature cells. We present a comparative transcriptome analysis of ex vivo isolated mouse multipotent hematopoietic stem/progenitor cells (Lin(neg)SCA-1(+)c-KIT(+)) and myeloid committed precursors (Lin(neg)SCA-1(neg)c-KIT(+)). Our data display dynamic transcriptional networks and identify a stem/progenitor gene expression pattern that is c ...[more]

PMID: 25418729

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Project description:Hamey2017 - Blood stem cell regulatory network This model is described in the article: Reconstructing blood stem cell regulatory network models from single-cell molecular profiles Fiona K. Hamey, Sonia Nestorowa, Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold Göttgens Proceedings of the National Academy of Sciences of the United States of America Abstract: Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships. This model is hosted on BioModels Database and identified by: MODEL1610060000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

Transcriptional landscape, long non-coding RNAs and post-transcriptional regulation in hematopoietic stem/progenitor cell differentiation

Publications

Transcriptome-wide profiling and posttranscriptional analysis of hematopoietic stem/progenitor cell differentiation toward myeloid commitment.

Similar Datasets

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