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Journal of Hematology and Oncology

, 10:27

First Online: 21 January 2017Received: 25 November 2016Accepted: 13 January 2017DOI: 10.1186-s13045-017-0401-7

Cite this article as: Ye, F., Huang, W. & Guo, G. J Hematol Oncol 2017 10: 27. doi:10.1186-s13045-017-0401-7

Abstract

Hematopoiesis is probably the best-understood stem cell differentiation system; hematopoietic stem cell HSC transplantation represents the most widely used regenerative therapy. The classical view of lineage hierarchy in hematopoiesis is built on cell type definition system by a group of cell surface markers. However, the traditional model is facing increasing challenges, as many classical cell types are proved to be heterogeneous. Recently, the developments of new technologies allow genome, transcriptome, proteome, and epigenome analysis at the single-cell level. For the first time, we can study hematopoietic system at single-cell resolution on a multi-omic scale. Here, we review recent technical advances in single-cell analysis technology, as well as their current applications. We will also discuss the impact of single-cell technologies on both basic research and clinical application in hematology.

KeywordsSingle-cell analysis Hematopoietic stem cell Lineage hierarchy Regulatory network AbbreviationsAGMAorta-gonad-mesonephros

ATAC-seqAssay for transposase-accessible chromatin with high-throughput sequencing

BasoBasophil

CLPCommon lymphoid progenitors

CMPCommon myeloid progenitors

CNVsCopy number variations

CTCsCirculating tumor cells

CyTOFCytometry by Time-Of-Flight

DCDendritic cells

DEPDielectrophoresis

DGEDigital gene expression matrix

EEmbryonic days

EosEosinophil

ErErythrocytes

FACSFluorescence-assisted cell sorting

GMPGranulo-monocyte progenitors

GranGranulocytes

Hi-CHigh-throughput-resolution chromosome conformation capture

HSCHematopoietic stem cell

HSPCHematopoietic stem and progenitor cells

IVTIn vitro transcription

LCMLaser capture microdissection

LyLymphoid

MALBACMultiple annealing and looping-based amplification cycles

MATLABMatrix laboratory

MDAMultiple displacement amplification

MegEMegakaryocytic and erythroid

MEPMegakaryocyte-erythroid progenitors

MkMegakaryocytes

MonoMonocytes

MPPMultipotent progenitors

mRNAMessenger RNA

mTORMechanistic targets of rapamycin

MyMyeloid

NeuNeutrophil

PCAPrincipal component analysis

scRRBSSingle-cell reduced representation bisulfite sequencing

SNPsSingle nucleotide polymorphisms

SPADESpanning-tree progression analysis of density-normalized events

t-SNEt-distributed stochastic neighbor embedding

UMIsUnique molecular identifiers

WGAWhole genome amplification

WGCNAWeighted gene co-expression network analysis

YSYolk sac

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Autor: Fang Ye - Wentao Huang - Guoji Guo

Fuente: https://link.springer.com/







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