Open AccessQuantifying the phenotypic information in mRNA abundance
Author(s) -
Maltz Evan,
Wollman Roy
Publication year - 2022
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.15252/msb.202211001
Subject(s) - biology , phenotype , abundance (ecology) , computational biology , genetics , messenger rna , evolutionary biology , gene , ecology
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 Ca 2+ signaling network and the dynamic Ca 2+ response in the same cell. We found that the overall expression levels of these 83 genes explain approximately 60% of Ca 2+ 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 Ca 2+ signaling. Our results provide the first direct quantification of information content about complex cellular phenotype that exists in mRNA abundance measurements.