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Transcriptional, epigenetic and retroviral signatures identify regulatory regions involved in hematopoietic lineage commitment.

Scientific reports | 2016

Genome-wide approaches allow investigating the molecular circuitry wiring the genetic and epigenetic programs of human somatic stem cells. Hematopoietic stem/progenitor cells (HSPC) give rise to the different blood cell types; however, the molecular basis of human hematopoietic lineage commitment is poorly characterized. Here, we define the transcriptional and epigenetic profile of human HSPC and early myeloid and erythroid progenitors by a combination of Cap Analysis of Gene Expression (CAGE), ChIP-seq and Moloney leukemia virus (MLV) integration site mapping. Most promoters and transcripts were shared by HSPC and committed progenitors, while enhancers and super-enhancers consistently changed upon differentiation, indicating that lineage commitment is essentially regulated by enhancer elements. A significant fraction of CAGE promoters differentially expressed upon commitment were novel, harbored a chromatin enhancer signature, and may identify promoters and transcribed enhancers driving cell commitment. MLV-targeted genomic regions co-mapped with cell-specific active enhancers and super-enhancers. Expression analyses, together with an enhancer functional assay, indicate that MLV integration can be used to identify bona fide developmentally regulated enhancers. Overall, this study provides an overview of transcriptional and epigenetic changes associated to HSPC lineage commitment, and a novel signature for regulatory elements involved in cell identity.

Pubmed ID: 27095295 RIS Download

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Cheng Li Lab of Computational Genomics (tool)

RRID:SCR_008613

Sponsor:
support is NIH grant R01 GM077122
National Institutes of Health, Claudia Adams Barr Program, and Friends of DFCI.
We are interested in how genomics changes promote cancer progression. Through collaboration with biomedical researchers, we analyze high-throughput microarray and sequencing data to study genomics, expression, and network changes in cancer cells. New methods are packaged into widely-used software such as dChip, which has been cited more than 1600 times.

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RRID:SCR_006442

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RRID:SCR_007673

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RRID:SCR_001237

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RRID:SCR_010843

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RRID:SCR_010881

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RRID:SCR_013504

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