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Integrated analysis of single-cell embryo data yields a unified transcriptome signature for the human pre-implantation epiblast.

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Stirparo, Giuliano G 
Boroviak, Thorsten 
Guo, Ge 


Single-cell profiling techniques create opportunities to delineate cell fate progression in mammalian development. Recent studies have provided transcriptome data from human pre-implantation embryos, in total comprising nearly 2000 individual cells. Interpretation of these data is confounded by biological factors, such as variable embryo staging and cell-type ambiguity, as well as technical challenges in the collective analysis of datasets produced with different sample preparation and sequencing protocols. Here, we address these issues to assemble a complete gene expression time course spanning human pre-implantation embryogenesis. We identify key transcriptional features over developmental time and elucidate lineage-specific regulatory networks. We resolve post-hoc cell-type assignment in the blastocyst, and define robust transcriptional prototypes that capture epiblast and primitive endoderm lineages. Examination of human pluripotent stem cell transcriptomes in this framework identifies culture conditions that sustain a naïve state pertaining to the inner cell mass. Our approach thus clarifies understanding both of lineage segregation in the early human embryo and of in vitro stem cell identity, and provides an analytical resource for comparative molecular embryology.



Embryo, Human, Pluripotency, RNA-seq, Single cell, Animals, Blastocyst, Blastocyst Inner Cell Mass, Cell Line, Cell Lineage, Chromosome Mapping, Embryo Culture Techniques, Embryonic Development, Gene Expression Profiling, Genetic Markers, Germ Layers, Humans, Pluripotent Stem Cells, Primates, Single-Cell Analysis

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The Company of Biologists
Medical Research Council (G1001028)
Wellcome Trust (097922/Z/11/Z)
Medical Research Council (MR/P00072X/1)
This work was supported by UK Biotechnology and Biological Sciences Research Council (BBSRC) research grant RG53615, UK Medical Research Council (MRC) programme grant G1001028, and institutional funding from the MRC and Wellcome Trust. AS is an MRC Professor.