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Quantifying the phenotypic information in mRNA abundance
Authors:Evan Maltz  Roy Wollman
Affiliation:1. Department of Chemistry and Biochemistry, UCLA, Los Angeles CA, USA ; 2. Institute of Quantitative and Computational Bioscience, UCLA, Los Angeles CA, USA ; 3. Department of Integrative Biology and Physiology, UCLA, Los Angeles CA, USA
Abstract:Quantifying the dependency between mRNA abundance and downstream cellular phenotypes is a fundamental open problem in biology. Advances in multimodal single‐cell measurement technologies provide an opportunity to apply new computational frameworks to dissect the contribution of individual genes and gene combinations to a given phenotype. Using an information theory approach, we analyzed multimodal data of the expression of 83 genes in the Ca2+ signaling network and the dynamic Ca2+ response in the same cell. We found that the overall expression levels of these 83 genes explain approximately 60% of Ca2+ signal entropy. The average contribution of each single gene was 17%, revealing a large degree of redundancy between genes. Using different heuristics, we estimated the dependency between the size of a gene set and its information content, revealing that on average, a set of 53 genes contains 54% of the information about Ca2+ signaling. Our results provide the first direct quantification of information content about complex cellular phenotype that exists in mRNA abundance measurements.
Keywords:cellular heterogeneity   gene expression   information theory   mutual information   signaling dynamics
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