2013
DOI: 10.1038/nsmb.2660
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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 … Show more

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Cited by 1,389 publications
(1,518 citation statements)
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References 59 publications
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“…To validate the predicted MXE candidates, we made use of over 15 billion publically available RNA‐Seq reads, selecting 515 samples comprising 31 tissues and organs, 12 cell lines and seven developmental stages (Barbosa‐Morais et al , 2012; Djebali et al , 2012; Tilgner et al , 2012; Xue et al , 2013; Yan et al , 2013; Fagerberg et al , 2014; Dataset EV1). The data were chosen to encompass common and rare potential splice events in a broad range of tissues, cell types and embryonic stages.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…To validate the predicted MXE candidates, we made use of over 15 billion publically available RNA‐Seq reads, selecting 515 samples comprising 31 tissues and organs, 12 cell lines and seven developmental stages (Barbosa‐Morais et al , 2012; Djebali et al , 2012; Tilgner et al , 2012; Xue et al , 2013; Yan et al , 2013; Fagerberg et al , 2014; Dataset EV1). The data were chosen to encompass common and rare potential splice events in a broad range of tissues, cell types and embryonic stages.…”
Section: Resultsmentioning
confidence: 99%
“…To understand the expression patterns of MXEs, we conducted a differential inclusion analysis using the Human Protein Atlas (Fagerberg et al , 2014), Embryonic Development (Yan et al , 2013) and ENCODE datasets (Djebali et al , 2012). Of the 1,399 MXEs, 608 MXEs (345 unique genes), 573 MXEs (389 unique genes) and 552 MXEs (330 unique genes) are differentially expressed, respectively (adjusted P ‐value < 0.05; Fig 3A, Appendix Figs S23–S26, Dataset EV5 and EV6).…”
Section: Resultsmentioning
confidence: 99%
“…Single-cell RNA-seq is now commonly used to study cell differentiation 15,24 . Here, we reanalyzed data from a single-cell RNA-seq experiment that was originally designed to study the differentiation of naive T cells into T H 2 cells 25 .…”
Section: Cell Cycle Variation Affects Global Gene Expressionmentioning
confidence: 99%
“…These protocols also allow the entire transcriptome of large numbers of single cells to be assayed in an unbiased way. This was initially done using microarrays 10,11 but is more often now done using next-generation sequencing [12][13][14][15] . Such approaches have been used to model early embryogenesis in the mouse 16 and to investigate bimodality in gene expression patterns of differentiating immune cell types 17 .…”
mentioning
confidence: 99%
“…Similar results have been obtained in other systems, such as the study of murine lung development, in which single cell transcriptomics data revealed cell‐type specific transcriptional regulators that discriminate between different populations that define the cellular hierarchy of the distal mouse lung epithelium 38. Single‐cell studies of the sub‐regions of the embryo, have also provided key insights of the initial phases of multicellular organisms development, allowing the identification of regulators triggering segregation between cell populations in early mouse embryos 39, and the delineation of gene regulatory mechanisms underlying progressive development of early mammalian embryos 40, 41. Profiling of the epigenetics landscape of individual cells has shown that lineage‐specific master regulators are associated with single‐cell epigenomic variability across several cell types, suggesting that control of single‐cell variance is a fundamental characteristic of different biological states 32.…”
Section: Single‐cell Profiling Is Key For Studying Pluripotent Statementioning
confidence: 99%