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Noisy cells are a good thing
Cells differentiate as the result of a long sequence of biochemical interactions. Differentiation ensures the correct tissue type and cell number will be made. Scientists at the Babraham Institute, EMBL-EBI and the Wellcome Trust-Medical Research Council Stem Cell Institute, examined stem cell genes from embryos at their earliest stages of development, a time when cells typically have matching patterns of gene activity with similar 'noise' levels. As variation in gene activity increases, different cells will have changes in noise levels based on the number of genes in that cell being activated.
The research is published in the journal Cell Reports.
One of the paper's co-first authors, Hisham Mohammed PhD, at the Babraham Institute, explains: "Our analyses suggest that elevated transcriptional noise at two key points in early development [formation of the primitive endoderm and epiblast] coincides with cell fate decisions. By contrast, after these decisions, cells become highly synchronised and grow rapidly. Our study systematically charts transcriptional noise and uncovers new processes associated with early lineage decisions."
The process of similar cells becoming different is called symmetry breaking. This study marks the first time the technique of single-cell sequencing was used to examine individual cells from mouse embryos in these early stages of development.."NewsAlerts">
"Making sense of the data generated in studies like this is only possible thanks to ongoing advances in computational biology. With more than 10,000 pieces of data being collected about each individual cell, modern computers are essential in achieving the level of sensitivity needed for this type of research," says John Marioni PhD of the EMBL-European Bioinformatics Institute (EMBL-EBI); Wellcome Trust Sanger Institute, Single-Cell Genomics Centre; and Cancer Research Institute at the University of Cambridge, all in Cambridge, UK, and lead computational scientist on the paper.
• A high-resolution scRNA-seq map of mouse from peri-implantation to early gastrulation
• Symmetry breaking genes and bivalent chromatin are linked to lineage fate at E4.5
• X chromosome inactivation correlates with Rlim and anticorrelates with Dnmt3a and Zfp57
• Polycomb targets are repressed in the E6.5 epiblast and activated in the primitive streak
The mouse inner cell mass (ICM) segregates into the epiblast and primitive endoderm (PrE) lineages coincident with implantation of the embryo. The epiblast subsequently undergoes considerable expansion of cell numbers prior to gastrulation. To investigate underlying regulatory principles, we performed systematic single-cell RNA sequencing (seq) of conceptuses from E3.5 to E6.5. The epiblast shows reactivation and subsequent inactivation of the X chromosome, with Zfp57 expression associated with reactivation and inactivation together with other candidate regulators. At E6.5, the transition from epiblast to primitive streak is linked with decreased expression of polycomb subunits, suggesting a key regulatory role. Notably, our analyses suggest elevated transcriptional noise at E3.5 and within the non-committed epiblast at E6.5, coinciding with exit from pluripotency. By contrast, E6.5 primitive streak cells became highly synchronized and exhibit a shortened G1 cell-cycle phase, consistent with accelerated proliferation. Our study systematically charts transcriptional noise and uncovers molecular processes associated with early lineage decisions.
Authors: Hisham Mohammed, Irene Hernando-Herraez, Aurora Savino, Antonio Scialdone, Iain Macaulay, Carla Mulas, Tamir Chandra, Thierry Voet, Wendy Dean, Jennifer Nichols'Correspondence information about the author Jennifer NicholsEmail the author Jennifer Nichols, John C. Marioni'Correspondence information about the author John C. MarioniEmail the author John C. Marioni, Wolf Reik
gastrulation, embryo, single-cell RNA-seq, epiblast, primitive endoderm, primitive streak, X-chromosome, transcriptional noise
Open access funded by Wellcome Trust
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Gene expression levels and variability of pluripotency factors classified into primed, naïve, and core genes (using previous classifications; Boroviak et al., 2014). The size of each dot represents gene expression levels, while variability is shown by color. Image credit: © 2017 The Author(s).