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      Single-Cell RNA-Seq Reveals Lineage and X Chromosome Dynamics in Human Preimplantation Embryos

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          Summary

          Mouse studies have been instrumental in forming our current understanding of early cell-lineage decisions; however, similar insights into the early human development are severely limited. Here, we present a comprehensive transcriptional map of human embryo development, including the sequenced transcriptomes of 1,529 individual cells from 88 human preimplantation embryos. These data show that cells undergo an intermediate state of co-expression of lineage-specific genes, followed by a concurrent establishment of the trophectoderm, epiblast, and primitive endoderm lineages, which coincide with blastocyst formation. Female cells of all three lineages achieve dosage compensation of X chromosome RNA levels prior to implantation. However, in contrast to the mouse, XIST is transcribed from both alleles throughout the progression of this expression dampening, and X chromosome genes maintain biallelic expression while dosage compensation proceeds. We envision broad utility of this transcriptional atlas in future studies on human development as well as in stem cell research.

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          Highlights

          • Transcriptomes of 1,529 individual cells from 88 human preimplantation embryos

          • Lineage segregation of trophectoderm, primitive endoderm, and pluripotent epiblast

          • X chromosome dosage compensation in the human blastocyst

          Abstract

          A comprehensive transcriptional map of human preimplantation development reveals a concurrent establishment of trophectoderm, epiblast, and primitive endoderm lineages and unique features of X chromosome dosage compensation in human.

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          Most cited references31

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          Gene action in the X-chromosome of the mouse (Mus musculus L.).

          MARY LYON (1961)
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            Accounting for technical noise in single-cell RNA-seq experiments.

            Single-cell RNA-seq can yield valuable insights about the variability within a population of seemingly homogeneous cells. We developed a quantitative statistical method to distinguish true biological variability from the high levels of technical noise in single-cell experiments. Our approach quantifies the statistical significance of observed cell-to-cell variability in expression strength on a gene-by-gene basis. We validate our approach using two independent data sets from Arabidopsis thaliana and Mus musculus.
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              Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst.

              Three distinct cell types are present within the 64-cell stage mouse blastocyst. We have investigated cellular development up to this stage using single-cell expression analysis of more than 500 cells. The 48 genes analyzed were selected in part based on a whole-embryo analysis of more than 800 transcription factors. We show that in the morula, blastomeres coexpress transcription factors specific to different lineages, but by the 64-cell stage three cell types can be clearly distinguished according to their quantitative expression profiles. We identify Id2 and Sox2 as the earliest markers of outer and inner cells, respectively. This is followed by an inverse correlation in expression for the receptor-ligand pair Fgfr2/Fgf4 in the early inner cell mass. Position and signaling events appear to precede the maturation of the transcriptional program. These results illustrate the power of single-cell expression analysis to provide insight into developmental mechanisms. The technique should be widely applicable to other biological systems. Copyright 2010 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                05 May 2016
                05 May 2016
                : 165
                : 4
                : 1012-1026
                Affiliations
                [1 ]Department of Clinical Science, Intervention and Technology, Karolinska Institutet, and Division of Obstetrics and Gynecology, Karolinska Universitetssjukhuset, 141 86 Stockholm, Sweden
                [2 ]Ludwig Institute for Cancer Research, Box 240, 171 77 Stockholm, Sweden
                [3 ]Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden
                [4 ]Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
                [5 ]Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
                Author notes
                []Corresponding author rickard.sandberg@ 123456ki.se
                [∗∗ ]Corresponding author fredrik.lanner@ 123456ki.se
                [6]

                Co-first author

                [7]

                Co-senior author

                Article
                S0092-8674(16)30280-X
                10.1016/j.cell.2016.03.023
                4868821
                27062923
                4d980a24-6efa-4577-8637-abc11a45d824
                © 2016 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 3 October 2015
                : 4 February 2016
                : 15 March 2016
                Categories
                Resource

                Cell biology
                Cell biology

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