Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process

Abstract

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.

Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells

“…We speculate that exit from a pluripotent cell state necessarily coincides with a phase of instability and increased gene expression variability, as demonstrated recently for lineage decisions in the hematopoietic system 57,58 . Based on our results we would like to propose tentative transcriptional signatures of such phases (Fig.…”

Cell Lineage Specification at Single Cell Resolution

“…These data suggest that there is possibility of increase transcriptional noise before lineage commitment as also observed in other systems [7,9].…”

Dynamic transcriptional signature and cell fate analysis reveals plasticity of individual neural plate border cells

“…These mixed-lineage states are generally achieved by expression of alternative lineage determinants like transcription factors and have been proposed to be mandatory steps in cell fate specification. Additionally, single-cell analysis of primary chicken erythroid progenitors revealed a peak of high cell-to-cell variability in gene expression, that precedes an irreversible commitment to differentiation, before being strongly decreased (Richard et al, 2016). …”