Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells
Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Single-cell RNA sequencing (RNA-Seq) analysis of 124 individual cells from human preimplantation embryos and embryonic stem cells (hESCs) now provides a com...
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| Published in | Nature structural & molecular biology Vol. 20; no. 9; pp. 1131 - 1139 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Nature Publishing Group US
01.09.2013
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Single-cell RNA sequencing (RNA-Seq) analysis of 124 individual cells from human preimplantation embryos and embryonic stem cells (hESCs) now provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs.
Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply single-cell RNA sequencing (RNA-Seq) analysis to 124 individual cells from human preimplantation embryos and human embryonic stem cells (hESCs) at different passages. The number of maternally expressed genes detected in our data set is 22,687, including 8,701 long noncoding RNAs (lncRNAs), which represents a significant increase from 9,735 maternal genes detected previously by cDNA microarray. We discovered 2,733 novel lncRNAs, many of which are expressed in specific developmental stages. To address the long-standing question whether gene expression signatures of human epiblast (EPI) and
in vitro
hESCs are the same, we found that EPI cells and primary hESC outgrowth have dramatically different transcriptomes, with 1,498 genes showing differential expression between them. This work provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs. |
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| AbstractList | Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply single-cell RNA sequencing (RNA-Seq) analysis to 124 individual cells from human preimplantation embryos and human embryonic stem cells (hESCs) at different passages. The number of maternally expressed genes detected in our data set is 22,687, including 8,701 long noncoding RNAs (lncRNAs), which represents a significant increase from 9,735 maternal genes detected previously by cDNA microarray. We discovered 2,733 novel lncRNAs, many of which are expressed in specific developmental stages. To address the long-standing question whether gene expression signatures of human epiblast (EPI) and in vitro hESCs are the same, we found that EPI cells and primary hESC outgrowth have dramatically different transcriptomes, with 1,498 genes showing differential expression between them. This work provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs. Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply single-cell RNA sequencing (RNA-Seq) analysis to 124 individual cells from human preimplantation embryos and human embryonic stem cells (hESCs) at different passages. The number of maternally expressed genes detected in our data set is 22,687, including 8,701 long noncoding RNAs (lncRNAs), which represents a significant increase from 9,735 maternal genes detected previously by cDNA microarray. We discovered 2,733 novel lncRNAs, many of which are expressed in specific developmental stages. To address the long-standing question whether gene expression signatures of human epiblast (EPI) and in vitro hESCs are the same, we found that EPI cells and primary hESC outgrowth have dramatically different transcriptomes, with 1,498 genes showing differential expression between them. This work provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs. [PUBLICATION ABSTRACT] Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply single-cell RNA sequencing (RNA-Seq) analysis to 124 individual cells from human preimplantation embryos and human embryonic stem cells (hESCs) at different passages. The number of maternally expressed genes detected in our data set is 22,687, including 8,701 long noncoding RNAs (lncRNAs), which represents a significant increase from 9,735 maternal genes detected previously by cDNA microarray. We discovered 2,733 novel lncRNAs, many of which are expressed in specific developmental stages. To address the long-standing question whether gene expression signatures of human epiblast (EPI) and in vitro hESCs are the same, we found that EPI cells and primary hESC outgrowth have dramatically different transcriptomes, with 1,498 genes showing differential expression between them. This work provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs.Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply single-cell RNA sequencing (RNA-Seq) analysis to 124 individual cells from human preimplantation embryos and human embryonic stem cells (hESCs) at different passages. The number of maternally expressed genes detected in our data set is 22,687, including 8,701 long noncoding RNAs (lncRNAs), which represents a significant increase from 9,735 maternal genes detected previously by cDNA microarray. We discovered 2,733 novel lncRNAs, many of which are expressed in specific developmental stages. To address the long-standing question whether gene expression signatures of human epiblast (EPI) and in vitro hESCs are the same, we found that EPI cells and primary hESC outgrowth have dramatically different transcriptomes, with 1,498 genes showing differential expression between them. This work provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs. Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Single-cell RNA sequencing (RNA-Seq) analysis of 124 individual cells from human preimplantation embryos and embryonic stem cells (hESCs) now provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs. Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply single-cell RNA sequencing (RNA-Seq) analysis to 124 individual cells from human preimplantation embryos and human embryonic stem cells (hESCs) at different passages. The number of maternally expressed genes detected in our data set is 22,687, including 8,701 long noncoding RNAs (lncRNAs), which represents a significant increase from 9,735 maternal genes detected previously by cDNA microarray. We discovered 2,733 novel lncRNAs, many of which are expressed in specific developmental stages. To address the long-standing question whether gene expression signatures of human epiblast (EPI) and in vitro hESCs are the same, we found that EPI cells and primary hESC outgrowth have dramatically different transcriptomes, with 1,498 genes showing differential expression between them. This work provides a comprehensive framework of the transcriptome landscapes of human early embryos and hESCs. |
| Audience | Academic |
| Author | Li, Rong Huang, Jin Li, Ming Tang, Fuchou Wu, Xinglong Yang, Lu Lian, Ying Wen, Lu Qiao, Jie Yan, Liying Zheng, Xiaoying Li, Ruiqiang Guo, Hongshan Wu, Jun Lao, Kaiqin Yan, Jie Yang, Mingyu Liu, Ping |
| Author_xml | – sequence: 1 givenname: Liying surname: Yan fullname: Yan, Liying organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University, Key Laboratory of Assisted Reproduction, Ministry of Education – sequence: 2 givenname: Mingyu surname: Yang fullname: Yang, Mingyu organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 3 givenname: Hongshan surname: Guo fullname: Guo, Hongshan organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 4 givenname: Lu surname: Yang fullname: Yang, Lu organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 5 givenname: Jun surname: Wu fullname: Wu, Jun organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 6 givenname: Rong surname: Li fullname: Li, Rong organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University, Key Laboratory of Assisted Reproduction, Ministry of Education – sequence: 7 givenname: Ping surname: Liu fullname: Liu, Ping organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 8 givenname: Ying surname: Lian fullname: Lian, Ying organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 9 givenname: Xiaoying surname: Zheng fullname: Zheng, Xiaoying organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 10 givenname: Jie surname: Yan fullname: Yan, Jie organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 11 givenname: Jin surname: Huang fullname: Huang, Jin organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 12 givenname: Ming surname: Li fullname: Li, Ming organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 13 givenname: Xinglong surname: Wu fullname: Wu, Xinglong organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 14 givenname: Lu surname: Wen fullname: Wen, Lu organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University – sequence: 15 givenname: Kaiqin surname: Lao fullname: Lao, Kaiqin organization: Genetic Systems, Applied Biosystems, Life Technologies – sequence: 16 givenname: Ruiqiang surname: Li fullname: Li, Ruiqiang email: lirq@pku.edu.cn organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University, Peking-Tsinghua Center for Life Sciences, College of Life Sciences, Peking University – sequence: 17 givenname: Jie surname: Qiao fullname: Qiao, Jie email: jie.qiao@263.net organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University, Key Laboratory of Assisted Reproduction, Ministry of Education – sequence: 18 givenname: Fuchou surname: Tang fullname: Tang, Fuchou email: tangfuchou@pku.edu.cn organization: Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23934149$$D View this record in MEDLINE/PubMed |
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| Snippet | Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Single-cell RNA... Measuring gene expression in individual cells is crucial for understanding the gene regulatory network controlling human embryonic development. Here we apply... |
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| SubjectTerms | 631/136/2086 631/136/532/2117 631/1647/514/1949 631/337/384/2568 Alternative Splicing Analysis Biochemistry Biological Microscopy Blastocyst - cytology Blastocyst - metabolism Blastomeres - cytology Blastomeres - metabolism Developmental stages DNA microarrays Embryo Culture Techniques Embryology Embryonic growth stage Embryonic stem cells Embryonic Stem Cells - cytology Embryonic Stem Cells - metabolism Embryos Female Gene expression Gene Expression Profiling Genetic aspects Germ Layers - cytology Germ Layers - metabolism Humans Life Sciences Membrane Biology Methods Molecular biology Oocytes - metabolism Physiological aspects Pluripotent Stem Cells - cytology Pluripotent Stem Cells - metabolism Protein Structure resource Ribonucleic acid RNA RNA sequencing RNA, Long Noncoding - genetics RNA, Long Noncoding - metabolism Sequence Analysis, RNA Single-Cell Analysis Stem cells Transcriptome |
| Title | Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells |
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