In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.

In somatic tissues, the CpG island of the imprinted Peg1/Mest gene is methylated on the maternal allele. We have examined the methylation of CpG and non-CpG sites of this differentially methylated CpG island in freshly ovulated oocytes, in vitro aged oocytes, and preimplantation embryos. The CpG methylation pattern was heterogeneous in freshly ovulated oocytes, despite the fact that they all were arrested in metaphase II. After short in vitro culture, Peg1/Mest became hypermethylated, whereas prolonged in vitro culture resulted in demethylation in a fraction of oocytes. Non-CpG methylation also occurred in a stage-specific manner. On alleles that were fully methylated at CpG sites, this modification was found, and it became reduced in twocell stage embryos and blastocysts. These observations suggest that the process of establishment of the methylation imprint at this locus is more dynamic than previously thought.Establishment of the mature epigenetic configuration of the genome is part of the maturation process of the gametes and is essential for normal development after fertilization. DNA methylation of CpG sites is one of the epigenetic modifications that regulates gene expression (for review, see (1)). The genome undergoes widespread changes in CpG methylation during germ cell maturation. Imprinted genes are of particular interest, because they are frequently associated with CpG-rich regions that are methylated differentially on the paternal and maternal chromosomes (for a review on imprinting, see Ref. 2). These differentially methylated regions (DMRs) 1 are believed to play an important role in the parental origin-dependent regulation of individual imprinted genes and of entire genomic regions during embryonic development. The methylation profile typical for the paternal or maternal chromosome is believed to be established during maturation of the male and female germ cells, but the exact kinetics of this process is still unclear. Some observations have even suggested that some imprinted genes reach their mature methylation profile only after fertilization (3).Peg1/Mest is a typical imprinted gene that is predominantly expressed from the paternal allele in the mesoderm and its derivatives (4). The methylation analysis of Peg1/Mest revealed that the CpG island in the promoter region was completely methylated on the maternal and unmethylated on the paternal chromosomes (5). It has been shown that the human PEG1/ MEST is already unmethylated in spermatogonia (6). In the maternal germ line, Peg1/Mest is fully methylated in ovulated oocytes that are arrested in metaphase of the second meiotic division (MII) (7).In a previous study (8), we have detected methylation heterogeneity in growing oocytes at several imprinted loci, including Peg1/Mest. The heterogeneity was substantially increased in the oocytes matured in vitro, suggesting that the methylation imprint, at this stage, is unstable and can be influenced by the cellular environment. In the present study, we investigated whether changes in the methylation ...

In this theory, cell differentiation is a two-step mechanism at each stage of development. In the first step, gene expression is unstable. It occurs stochastically and produces different cell types. In the second step gene expression is stabilized by means of cellular interactions. However, this stabilization cannot occur until the combination of cell phenotypes corresponding to the developmental stage is expressed. This selection mechanism prevents disorganizing consequences of stochasticity in gene expression and directs the embryo towards the adult stage. Instability and stochasticity in gene expression are caused by random displacement of regulators along DNA, whereas phosphorylation and/or dephosphorylation of transcriptional regulators triggered by signal transduction between cells are responsible for the stabilization of stochastic gene expression. The origin of cellular differentiation is explained as an adaptation of cells to metabolic gradients created by substrate diffusion inside growing cell populations. This mechanism provides cells with complementary metabolism, increasing their ability to use food resources. Because the metabolic gradients are dependent on external substrate concentrations, cellular differentiation can also be viewed as an extension of natural selection inside organisms.

BackgroundA number of studies have established that stochasticity in gene expression may play an important role in many biological phenomena. This therefore calls for further investigations to identify the molecular mechanisms at stake, in order to understand and manipulate cell-to-cell variability. In this work, we explored the role played by chromatin dynamics in the regulation of stochastic gene expression in higher eukaryotic cells.ResultsFor this purpose, we generated isogenic chicken-cell populations expressing a fluorescent reporter integrated in one copy per clone. Although the clones differed only in the genetic locus at which the reporter was inserted, they showed markedly different fluorescence distributions, revealing different levels of stochastic gene expression. Use of chromatin-modifying agents showed that direct manipulation of chromatin dynamics had a marked effect on the extent of stochastic gene expression. To better understand the molecular mechanism involved in these phenomena, we fitted these data to a two-state model describing the opening/closing process of the chromatin. We found that the differences between clones seemed to be due mainly to the duration of the closed state, and that the agents we used mainly seem to act on the opening probability.ConclusionsIn this study, we report biological experiments combined with computational modeling, highlighting the importance of chromatin dynamics in stochastic gene expression. This work sheds a new light on the mechanisms of gene expression in higher eukaryotic cells, and argues in favor of relatively slow dynamics with long (hours to days) periods of quiet state.