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Studying hematopoiesis using single-cell technologies

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 surf...

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Detalles Bibliográficos
Autores principales: Ye, Fang, Huang, Wentao, Guo, Guoji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5251333/
https://www.ncbi.nlm.nih.gov/pubmed/28109325
http://dx.doi.org/10.1186/s13045-017-0401-7
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author Ye, Fang
Huang, Wentao
Guo, Guoji
author_facet Ye, Fang
Huang, Wentao
Guo, Guoji
author_sort Ye, Fang
collection PubMed
description 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.
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spelling pubmed-52513332017-01-26 Studying hematopoiesis using single-cell technologies Ye, Fang Huang, Wentao Guo, Guoji J Hematol Oncol Review 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. BioMed Central 2017-01-21 /pmc/articles/PMC5251333/ /pubmed/28109325 http://dx.doi.org/10.1186/s13045-017-0401-7 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Review
Ye, Fang
Huang, Wentao
Guo, Guoji
Studying hematopoiesis using single-cell technologies
title Studying hematopoiesis using single-cell technologies
title_full Studying hematopoiesis using single-cell technologies
title_fullStr Studying hematopoiesis using single-cell technologies
title_full_unstemmed Studying hematopoiesis using single-cell technologies
title_short Studying hematopoiesis using single-cell technologies
title_sort studying hematopoiesis using single-cell technologies
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5251333/
https://www.ncbi.nlm.nih.gov/pubmed/28109325
http://dx.doi.org/10.1186/s13045-017-0401-7
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