Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing

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Abstract

Background

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved.

Results

We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells.

Conclusions

Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1426-0) contains supplementary material, which is available to authorized users.

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Most cited references 33

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featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

, , (2013)

Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

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Naive and primed pluripotent states.

Jennifer Nichols, Austin Smith (2009)

After maternal predetermination gives way to zygotic regulation, a ground state is established within the mammalian embryo. This tabula rasa for embryogenesis is present only transiently in the preimplantation epiblast. Here, we consider how unrestricted cells are first generated and then prepared for lineage commitment. We propose that two phases of pluripotency can be defined: naive and primed. This distinction extends to pluripotent stem cells derived from embryos or by molecular reprogramming ex vivo.

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The technology and biology of single-cell RNA sequencing.

Aleksandra A. Kolodziejczyk, Jong Kim, Valentine Svensson … (2015)

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications.

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Author and article information

Contributors

Haide Chen: hyde@zju.edu.cn

Guo-Cheng Yuan: gcyuan@jimmy.harvard.edu

Guoji Guo: ggj@zju.edu.cn

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 5 April 2018

Publication date PMC-release: 5 April 2018

Publication date Collection: 2018

Volume: 19

Electronic Location Identifier: 47

Affiliations

[1 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, Center for Stem Cell and Regenerative Medicine, , Zhejiang University School of Medicine, ; Hangzhou, 310058 China

[2 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, Institute of Hematology, The 1st Affiliated Hospital, , Zhejiang University School of Medicine, ; Hangzhou, 310003 China

[3 ]Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Zhejiang Provincial Key Lab for Tissue Engineering and Regenerative Medicine, Hangzhou, 310058 China

[4 ]Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard Chan School of Public Health, Boston, MA 02115 USA

[5 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, College of Animal Science, , Zhejiang University, ; Hangzhou, 310058 China

[6 ]ISNI 0000000123704535, GRID grid.24516.34, Department of Computer Science and Technology, , Tongji University, ; Shanghai, 201804 China

[7 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, College of Life Sciences, , Zhejiang University, ; Hangzhou, 310058 China

[8 ]ISNI 0000 0004 1759 700X, GRID grid.13402.34, Stem Cell Institute, , Zhejiang University, ; Hangzhou, 310058 China

Article

Publisher ID: 1426

DOI: 10.1186/s13059-018-1426-0

PMC ID: 5887227

PubMed ID: 29622030

SO-VID: 81c7794d-06b7-450a-80b4-3ea6282457c9

License:

Open Access This 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.

History

Date received : 29 November 2017

Date accepted : 21 March 2018

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 81770188

Award ID: 31722027

Award ID: 31701290

Award Recipient : Guoji Guo

Funded by: Fundamental Research Funds for the Central Universities

Award ID: 2016XZZX002-04

Award Recipient : Guoji Guo

Funded by: National Key Program on Stem Cell and Translational Research

Award ID: 2017YFA0103401

Award Recipient : Guoji Guo

Funded by: 973 Program

Award ID: 2015CB964900

Award Recipient : Guoji Guo

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: single-cell rna-sequencing,primed human pluripotent stem cell,embryoid body,naïve human pluripotent stem cell

Data availability:

ScienceOpen disciplines: Genetics

Keywords: single-cell rna-sequencing, primed human pluripotent stem cell, embryoid body, naïve human pluripotent stem cell

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing

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Abstract

Background

Results

Conclusions

Electronic supplementary material

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Evolutionary Cell Biology

Most cited references 33

featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

Naive and primed pluripotent states.

The technology and biology of single-cell RNA sequencing.

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Contributors

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History

Funding

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