Abstract
Variability in gene expression across a population of homogeneous cells is known to influence various biological processes. In model organisms, natural genetic variants were found that modify expression dispersion (variability at a fixed mean) but very few studies have detected such effects in humans. Here, we analyzed single-cell expression of four proteins (CD23, CD55, CD63 and CD86) across cell lines derived from individuals of the Yoruba population. Using data from over 30 million cells, we found substantial inter-individual variation of dispersion. We demonstrate, via de novo cell line generation and subcloning experiments, that this variation exceeds the variation associated with cellular immortalization. We detected a genetic association between the expression dispersion of CD63 and the rs971 SNP. Our results show that human DNA variants can have inherently-probabilistic effects on gene expression. Such subtle genetic effects may participate to phenotypic variation and disease outcome.
Highlights
Variability in gene expression across a population of homogeneous cells is known to influence various biological processes
Together with freshly-generated lymphoblastoid cell lines (LCLs) and subcloning experiments, we found that the level of expression dispersion of four cell-surface proteins differs between individuals
The advantage of lymphoblastoid cells is that they express many B cell-specific cell-surface proteins, for which monoclonal antibodies have been developed and that can be quantified on single cells
Summary
Variability in gene expression across a population of homogeneous cells is known to influence various biological processes. Natural genetic variants were found that modify expression dispersion (variability at a fixed mean) but very few studies have detected such effects in humans. Our results show that human DNA variants can have inherently-probabilistic effects on gene expression Such subtle genetic effects may participate to phenotypic variation and disease outcome. We previously introduced the concept of single-cell Probabilistic Trait Loci (scPTL)[2] This term is analogous to Quantitative Trait Loci (QTLs) but defines genetic variants that control single-cell traits in ways that can be more subtle than changing the trait’s mean. Even if single-cell data can provide fine-scale descriptions of the genetic control of gene expression[16], loci affecting variability are sometimes identified because of their effect on mean expression[17]. Primary T cells comprise a complex mixture of cells, and could possibly include various sources of heterogeneities
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