Abstract

Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τT, that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance . Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk.

Highlights

  • The phenotypic variation among organisms or cells is a theme of growing importance in biology

  • We develop a theoretical framework based on a stochastic model and put it to work in the analysis of T cell receptor expression level in CD4 T cells

  • We show that T cell populations with genetically diverse receptors display stable variation in receptor expression but, surprisingly, we detect persistent differences in receptor levels among uniform transgenic T cells

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Summary

Introduction

The phenotypic variation among organisms or cells is a theme of growing importance in biology. The increasing availability of single-cell resolution genomics, proteomics and metabolomics technologies has enabled molecular biologists to analyse cell lineages and tissues showing that what were previously perceived as homogeneous cell populations are a complex mixture of often transient and interchangeable cellular types and cellular states (see discussion in [3]) In parallel to these studies linking phenotypes to genotype, the literature on stochastic gene expression [4,5,6,7,8], reviewed in [9], has brought to light the variation in expression levels in isogenic cells, even when these are in the same cellular state and in the same environment. The variation is typically attributed to the “noise” resulting from the small copy number of molecules involved in the process

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