Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels - Institut Pasteur Access content directly
Journal Articles PLoS Genetics Year : 2020

Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Abstract

Genetic variation can change how much a gene is turned on or off in a tissue or a population of cells of the same type. However, this averaging of expression levels across a cell population masks an important aspect of gene expression regulation, namely its variability. Recent work in humans has indicated that nearby (cis) genetic factors minimally influence this variability. We have combined genetic measurements with flow cytometry single-cell protein levels to resolve the genetic control of gene expression variability in human immune cells. Importantly, we have demonstrated that whilst genetic variants near the target genes (cis) rarely influence variability, there is still an extensive genetic contribution from genetic loci faraway, or on a separate chromosome (trans). Furthermore, we have resolved that these trans genetic effects regulate the expression of other nearby genes, which leads to changes in gene expression variability of our target proteins. Our findings can be explained by an evolutionary balance between the cis regulation of gene expression levels, and the downstream consequences on gene expression variability.
Fichier principal
Vignette du fichier
Morgan_Plos Genetics 2020.pdf (1.33 Mo) Télécharger le fichier
Origin : Publication funded by an institution
Loading...

Dates and versions

pasteur-02549831 , version 1 (21-04-2020)

Licence

Attribution

Identifiers

Cite

Michael D Morgan, Etienne Patin, Bernd Jagla, Milena Hasan, Lluis Quintana-Murci, et al.. Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels. PLoS Genetics, 2020, 16 (3), pp.e1008686. ⟨10.1371/journal.pgen.1008686⟩. ⟨pasteur-02549831⟩
32 View
85 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More