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Of gene expression and cell division time: a mathematical framework for advanced differential gene expression and data analysis

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Item Type:Article
Title:Of gene expression and cell division time: a mathematical framework for advanced differential gene expression and data analysis
Creators Name:Baum, K. and Schuchhardt, J. and Wolf, J. and Busse, D.
Abstract:Estimating fold changes of average mRNA and protein molecule counts per cell is the most common way to perform differential expression analysis. However, these gene expression data may be affected by cell division, an often-neglected phenomenon. Here, we develop a quantitative framework that links population-based mRNA and protein measurements to rates of gene expression in single cells undergoing cell division. The equations we derive are easy-to-use and widely robust against biological variability. They integrate multiple "omics" data into a coherent, quantitative description of single-cell gene expression and improve analysis when comparing systems or states with different cell division times. We explore these ideas in the context of resting versus activated B cells. Analyzing differences in protein synthesis rates enables to account for differences in cell division times. We demonstrate that this improves the resolution and hit rate of differential gene expression analysis when compared to analyzing population protein abundances alone.
Keywords:Age Distribution of Cell Population, B Cell Activation, Cell Division Time, Differential Gene Expression Analysis, Half-Lives, Mathematical Modeling, Mass Spectrometry, Omics Data Integration, Population and Single-Cell Gene Expression, RNA Sequencing
Source:Cell Systems
ISSN:2405-4712
Publisher:Cell Press / Elsevier (U.S.A.)
Date:11 September 2019
Official Publication:https://doi.org/10.1016/j.cels.2019.07.009
PubMed:View item in PubMed

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