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Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells

Nature Structural & Molecular Biology volume 20, pages 11311139 (2013) | Download Citation

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.

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References

  1. 1.

    & Gene expression heterogeneities in embryonic stem cell populations: origin and function. Curr. Opin. Cell Biol. 23, 650–656 (2011).

  2. 2.

    et al. Future developments in assisted reproduction in humans. Reproduction 123, 171–183 (2002).

  3. 3.

    , , , & Human pre-implantation embryo development. Development 139, 829–841 (2012).

  4. 4.

    Non-invasive imaging of human embryos to predict developmental competence. Placenta 32 (Suppl. 3), S264–S267 (2011).

  5. 5.

    et al. Comparative transcriptome analysis of human trophectoderm and embryonic stem cell-derived trophoblasts reveal key participants in early implantation. Biol. Reprod. 86, 1–21 (2012).

  6. 6.

    et al. Dynamic changes in gene expression during human early embryo development: from fundamental aspects to clinical applications. Hum. Reprod. Update 17, 272–290 (2011).

  7. 7.

    et al. Transcriptome analysis during human trophectoderm specification suggests new roles of metabolic and epigenetic genes. PLoS ONE 7, e39306 (2012).

  8. 8.

    et al. A gene expression signature shared by human mature oocytes and embryonic stem cells. BMC Genomics 10, 10 (2009).

  9. 9.

    et al. Dissecting the first transcriptional divergence during human embryonic development. Stem Cell Rev. Rep. 8, 150–162 (2012).

  10. 10.

    et al. The unique transcriptome through day 3 of human preimplantation development. Hum. Mol. Genet. 13, 1461–1470 (2004).

  11. 11.

    et al. Functional genomics of 5- to 8-cell stage human embryos by blastomere single-cell cDNA analysis. PLoS ONE 5, e13615 (2010).

  12. 12.

    et al. Transcriptome analysis reveals dialogues between human trophectoderm and endometrial cells during the implantation period. Hum. Reprod. 26, 1440–1449 (2011).

  13. 13.

    et al. Waves of early transcriptional activation and pluripotency program initiation during human preimplantation development. Development 138, 3699–3709 (2011).

  14. 14.

    et al. Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage. Nat. Biotechnol. 28, 1115–1121 (2010).

  15. 15.

    et al. Rewirable gene regulatory networks in the preimplantation embryonic development of three mammalian species. Genome Res. 20, 804–815 (2010).

  16. 16.

    et al. Evidence that human blastomere cleavage is under unique cell cycle control. J. Assist. Reprod. Genet. 26, 187–195 (2009).

  17. 17.

    et al. Genome-wide microarray evidence that 8-cell human blastomeres over-express cell cycle drivers and under-express checkpoints. J. Assist. Reprod. Genet. 27, 265–276 (2010).

  18. 18.

    & Modular regulatory principles of large non-coding RNAs. Nature 482, 339–346 (2012).

  19. 19.

    et al. Embryonic stem cell lines derived from human blastocysts. Science 282, 1145–1147 (1998).

  20. 20.

    et al. Gene expression profiles of human inner cell mass cells and embryonic stem cells. Differentiation 78, 18–23 (2009).

  21. 21.

    et al. Tracking the progression of the human inner cell mass during embryonic stem cell derivation. Nat. Biotechnol. 30, 278–282 (2012).

  22. 22.

    et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–382 (2009).

  23. 23.

    , & Development and applications of single-cell transcriptome analysis. Nat. Methods 8, S6–S11 (2011).

  24. 24.

    et al. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat. Biotechnol. 30, 777–782 (2012).

  25. 25.

    , , & CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Reports 2, 666–673 (2012).

  26. 26.

    et al. Tracing the derivation of embryonic stem cells from the inner cell mass by single-cell RNA-Seq analysis. Cell Stem Cell 6, 468–478 (2010).

  27. 27.

    , & Human gene expression first occurs between the four- and eight-cell stages of preimplantation development. Nature 332, 459–461 (1988).

  28. 28.

    & Making the blastocyst: lessons from the mouse. J. Clin. Invest. 120, 995–1003 (2010).

  29. 29.

    & Blastocyst lineage formation, early embryonic asymmetries and axis patterning in the mouse. Development 136, 701–713 (2009).

  30. 30.

    et al. An alternative splicing switch regulates embryonic stem cell pluripotency and reprogramming. Cell 147, 132–146 (2011).

  31. 31.

    et al. Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proc. Natl. Acad. Sci. USA 106, 11667–11672 (2009).

  32. 32.

    et al. Long noncoding RNAs with enhancer-like function in human cells. Cell 143, 46–58 (2010).

  33. 33.

    & Molecular mechanisms of long noncoding RNAs. Mol. Cell 43, 904–914 (2011).

  34. 34.

    et al. lincRNAs act in the circuitry controlling pluripotency and differentiation. Nature 477, 295–300 (2011).

  35. 35.

    , & The long non-coding RNAs (lncRNAs): a new (p)layer in the “dark matter”. Frontiers Genet. 2, 107 (2012).

  36. 36.

    et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).

  37. 37.

    et al. CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Res. 35, W345-9 (2007).

  38. 38.

    et al. Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 25, i54–i62 (2009).

  39. 39.

    et al. Ab initio reconstruction of transcriptomes of pluripotent and lineage committed cells reveals gene structures of thousands of lincRNAs. Nat. Biotechnol. 28, 503–510 (2010).

  40. 40.

    & Gene expression profiling of human oocytes at different maturational stages and after in vitro maturation. Am. J. Obstet. Gynecol. 198, 455.e1–455.e11 (2008).

  41. 41.

    et al. Human hypoblast formation is not dependent on FGF signalling. Dev. Biol. 361, 358–363 (2012).

  42. 42.

    et al. Derivation of pluripotent epiblast stem cells from mammalian embryos. Nature 448, 191–195 (2007).

  43. 43.

    et al. New cell lines from mouse epiblast share defining features with human embryonic stem cells. Nature 448, 196–199 (2007).

  44. 44.

    et al. Core transcriptional regulatory circuitry in human embryonic stem cells. Cell 122, 947–956 (2005).

  45. 45.

    & Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22, 1540–1542 (2006).

  46. 46.

    et al. Characteristics of embryo development in Robertsonian translocations' preimplantation genetic diagnosis cycles. Prenat. Diagn. 29, 1167–1170 (2009).

  47. 47.

    et al. RNA-seq analysis to capture the transcriptome landscape of a single cell. Nat. Protoc. 5, 516–535 (2010).

  48. 48.

    & Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

  49. 49.

    et al. NONCODE v3.0: integrative annotation of long noncoding RNAs. Nucleic Acids Res. D210-5 (2012).

  50. 50.

    et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29, 644–652 (2011).

  51. 51.

    et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 31, 5654–5666 (2003).

  52. 52.

    BLAT—The BLAST-Like Alignment Tool. Genome Res. 12, 656–664 (2002).

  53. 53.

    , & Methods of embryo scoring in in vitro fertilization. Reprod. Biol. 4, 5–22 (2004).

  54. 54.

    , & Na/K-ATPase β1 subunit expression is required for blastocyst formation and normal assembly of trophectoderm tight junction-associated proteins. J. Biol. Chem. 282, 12127–12134 (2007).

  55. 55.

    et al. Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst. Dev. Cell 18, 675–685 (2010).

  56. 56.

    et al. Epigenetic reversion of post-implantation epiblast to pluripotent embryonic stem cells. Nature 461, 1292–1295 (2009).

  57. 57.

    & The significance of digital gene expression profiles. Genome Res. 7, 986–995 (1997).

  58. 58.

    , , , & Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–628 (2008).

  59. 59.

    , , & Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863–14868 (1998).

  60. 60.

    Java Treeview—extensible visualization of microarray data. Bioinformatics 20, 3246–3248 (2004).

  61. 61.

    & Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Stat. Soc. B 57, 289–300 (1995).

  62. 62.

    , & Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2008).

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Acknowledgements

F.T. was supported by grants from the National Basic Research Program of China (2012CB966704 and 2011CB966303) and National Natural Science Foundation of China (31271543). J.Q. was supported by grants from the National Basic Research Program of China (2011CB944500) and the National Natural Science Funds for Distinguished Young Scholar (30825038). L.Y. was supported by a grant from the National Science Foundation of China (81000275). We would like to thank S. Gao, Y. Zhang, P. Xu, S. Lin, X. Ren, Q. Zhang, Y. Jiang, M. Fan, J. Li, X. Zhuang, W. Song and Y. Chen for their great help.

Author information

Author notes

    • Liying Yan
    •  & Mingyu Yang

    These authors contributed equally to this work.

Affiliations

  1. Biodynamic Optical Imaging Center and Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University, Beijing, China.

    • Liying Yan
    • , Mingyu Yang
    • , Hongshan Guo
    • , Lu Yang
    • , Jun Wu
    • , Rong Li
    • , Ping Liu
    • , Ying Lian
    • , Xiaoying Zheng
    • , Jie Yan
    • , Jin Huang
    • , Ming Li
    • , Xinglong Wu
    • , Lu Wen
    • , Ruiqiang Li
    • , Jie Qiao
    •  & Fuchou Tang
  2. Key Laboratory of Assisted Reproduction, Ministry of Education, Beijing, China.

    • Liying Yan
    • , Rong Li
    •  & Jie Qiao
  3. Genetic Systems, Applied Biosystems, Life Technologies, Foster City, California, USA.

    • Kaiqin Lao
  4. Peking-Tsinghua Center for Life Sciences, College of Life Sciences, Peking University, Beijing, China.

    • Ruiqiang Li

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Contributions

J.Q. and F.T. conceived and designed the project, and R.L. was in charge of the bioinformatic analysis. L. Yan, H.G., L. Yang, X.W. and L.W. conducted the majority of the experiments. M.Y. and J.W. did all of the data analysis. R.L., P.L., Y.L., X.Z., J.Y., J.H. and M.L. contributed to oocyte collection, sperm treatment and embryo culture in vitro. L. Yan, M.Y., K.L., R.L., J.Q. and F.T. prepared the manuscript. All authors contributed to the revision of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ruiqiang Li or Jie Qiao or Fuchou Tang.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–7 and Supplementary Note

Excel files

  1. 1.

    Supplementary Table 1

    Expression (RPKM) of known RefSeq genes in 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

  2. 2.

    Supplementary Table 2

    Expression (RPKM) of known RefSeq transcripts in 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

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    Supplementary Table 3

    GO enrichment analysis for EPI-specific genes compared to all the other cells after the 8-cell stage (including 8-cell–stage embryos).

  4. 4.

    Supplementary Table 4

    Number of exon-exon junction reads that are unique to transcript isoforms of known RefSeq genes in 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

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    Supplementary Table 5

    Expression (counts) of known lncRNA genes in 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

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    Supplementary Table 6

    Expression (counts) of novel transcripts in 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

  7. 7.

    Supplementary Table 7

    Expression (RPKM) of the differentially expressed genes among the epiblast (EPI), primitive endoderm (PE) and trophectoderm (TE) lineages of late blastocysts.

  8. 8.

    Supplementary Table 8

    Expression (RPKM) of the differentially expressed genes between the epiblast (EPI) cells of late blastocysts and passage #0 hESCs.

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    Supplementary Table 9

    The rRNA contamination in the single cell RNA-Seq data for 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

  10. 10.

    Supplementary Table 10

    Summary of the sequencing exercise, quality control (Q20 and Q30 percentage of the sequencing reads) and mapped rates of RNA-Seq data to RefSeq, Ensemble, known lncRNAs, and genome of 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

  11. 11.

    Supplementary Table 11

    The distribution of all mapped reads in different features (exon, intron and intergenic) of the human genome in 124 single cells from mature oocytes, preimplantation embryos and embryonic stem cells.

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DOI

https://doi.org/10.1038/nsmb.2660

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