Independent regulation of gene expression level and noise by histone modifications

Abstract

The inherent stochasticity generates substantial gene expression variation among isogenic cells under identical conditions, which is frequently referred to as gene expression noise or cell-to-cell expression variability. Similar to (average) expression level, expression noise is also subject to natural selection. Yet it has been observed that noise is negatively correlated with expression level, which manifests as a potential constraint for simultaneous optimization of both. Here, we studied expression noise in human embryonic cells with computational analysis on single-cell RNA-seq data and in yeast with flow cytometry experiments. We showed that this coupling is overcome, to a certain degree, by a histone modification strategy in multiple embryonic developmental stages in human, as well as in yeast. Importantly, this epigenetic strategy could fit into a burst-like gene expression model: promoter-localized histone modifications (such as H3K4 methylation) are associated with both burst size and burst frequency, which together influence expression level, while gene-body-localized ones (such as H3K79 methylation) are more associated with burst frequency, which influences both expression level and noise. We further knocked out the only “writer” of H3K79 methylation in yeast, and observed that expression noise is indeed increased. Consistently, dosage sensitive genes, such as genes in the Wnt signaling pathway, tend to be marked with gene-body-localized histone modifications, while stress responding genes, such as genes regulating autophagy, tend to be marked with promoter-localized ones. Our findings elucidate that the “division of labor” among histone modifications facilitates the independent regulation of expression level and noise, extend the “histone code” hypothesis to include expression noise, and shed light on the optimization of transcriptome in evolution.

Multivariable regulation of gene expression plasticity in metazoans

“…Consistent with this, the TATA box promoter element is positively correlated with both gene expression plasticity and cell-to-cell expression noise (4,44). Recent studies have also identified certain types of histone modification as significantly associated with expression noise (44,45), some of which were independently identified here to regulate expression plasticity. However, closer examination of the relationship between noise and plasticity demonstrates that the coupling between the two is highly conditional and evolvable in both yeast (4) and E. coli (46).…”

“…Furthermore, while H3K27me3, H3K4me1, and H3K9ac are associated with high expression noise in mouse embryonic stem cells (44), we found that these modifications do not affect expression plasticity. Interestingly, H3K36me3, H3K79me2, and H4K20me1 have been independently identified as significantly associated with restricted expression noise (45) and plasticity (Figure 6).…”

“…(C) Scatter plot shows correlation between GEP and gene expression noise in which the same types of histone modifications are identified to restrict GEP and expression noise respectively. As in the previous study (45), coefficients of variation of gene expression levels in 94 single mESCs cultured under 2i+LIF conditions (48) were used to quantify expression noise.…”

Role of noise and parametric variation in the dynamics of gene regulatory circuits

“…Both gene expression noise and parametric variations are common in biological systems 1,4,6,7,13,22,48 . On the one hand, the Gillespie algorithm (Fig S2) has been used to model the stochastic dynamics of gene expression caused by low copy number and slow switches between gene states 16 .…”

“…Noise or stochastic fluctuations in molecular components have been shown to play important role in many biological processes [1][2][3] , such as phenotypic switching, gene expression coordination, cell cycle and cell differentiation 4 , in both prokaryotic 5 and eukaryotic organisms 3,4,6,7 . Noise can propagate in a gene network with a cascade of circuit motifs, and the expression level of a gene can vary up to six orders of magnitude between cells 1,8 .…”