Systematic Analysis of the Determinants of Gene Expression Noise in Embryonic Stem Cells

Abstract

Isogenic cells in a common environment show substantial cell-to-cell variation in gene expression, often referred to as "expression noise." Here, we use multiple single-cell RNA-sequencing datasets to identify features associated with high or low expression noise in mouse embryonic stem cells. These include the core promoter architecture of a gene, with CpG island promoters and a TATA box associated with low and high noise, respectively. High noise is also associated with "conflicting" chromatin states-the absence of transcription-associated histone modifications or the presence of repressive ones in active genes. Genes regulated by pluripotency factors through super-enhancers show high and correlated expression variability, consistent with fluctuations in the pluripotent state. Together, our results provide an integrated view of how core promoters, chromatin, regulation, and pluripotency fluctuations contribute to the variability of gene expression across individual stem cells.

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

“…Furthermore, the correlation structure between variability and other features must be taken into account. For example, increased gene expression variability is associated with transcript length, while the number of expressed transcripts shows a strong negative correlation with gene expression variability . Technical variability due to intrinsic experimental noise is greater for lowly expressed genes than for those expressed at high levels .…”

“…Related to aging, variability also occurs over an individual's lifetime due to development, growth, pregnancy, and menopause. At the cellular level, the distinct stage of the cell cycle is another important source of variability …”

“…Chromatin properties at gene promoters and bodies can impact transcriptional variation . TATA boxes are sequence motifs that can be found at the promoters of genes displaying variability and plasticity in changing environments.…”

“…At the cellular level, the distinct stage of the cell cycle is another important source of variability. [44,45,46]…”

Ribosome stoichiometry: from form to function.

“…If post-transcriptional mechanisms did not actively buffer mRNA variability, these large fold changes would propagate to the protein levels. One buffering mechanism may involve microRNAs or other translational regulators such as RNA binding proteins (RBPs) [48]. Another mechanism may involve proteins interacting with specialized ribosomes and exerting direct feedback on the translation of their mRNAs and thus buffer the inevitable transcriptional noise.…”