TITLE: “Phenotypic consequences of gene expression variability.”
ABSTRACT: The central dogma of biology proposes that information flows from genes to RNA to protein, determining protein identity and abundance. Single cell transcriptome measurements provide ample information about RNA abundance in cells. While the expression of individual genes clearly matters for determining phenotype, they do not work independently. How the information in RNA abundances is combined to determine cellular phenotype remains unclear. Here we address this question for a single cellular phenotype, the dynamic Ca2+ signaling response to a ligand. Using an information theory approach, we estimated the mutual information between the expression of subsets of 83 genes in the Ca2+ signaling network and the dynamic Ca2+ response in the same cell. We found a high degree of dependency that corresponds to 60% of Ca2+ signal entropy, yet most genes have redundant information. Furthermore, a relatively small group of genes preserve most of the dependency. Our results demonstrate a high degree of regulatory elasticity with small changes in RNA abundance informing an emergent cellular phenotype.
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