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• W2274308875 abstract "Gene expression heterogeneity contributes to development as well as disease progression. Due to technological limitations, most studies to date have focused on differences in mean expression across experimental conditions, rather than differences in gene expression variance. The advent of single cell RNA sequencing has now made it feasible to study gene expression heterogeneity and to characterise genes based on their coefficient of variation.We collected single cell gene expression profiles for 32 human and 39 mouse embryonic stem cells and studied correlation between diverse characteristics such as network connectivity and coefficient of variation (CV) across single cells. We further systematically characterised properties unique to High CV genes.Highly expressed genes tended to have a low CV and were enriched for cell cycle genes. In contrast, High CV genes were co-expressed with other High CV genes, were enriched for bivalent (H3K4me3 and H3K27me3) marked promoters and showed enrichment for response to DNA damage and DNA repair.Taken together, this analysis demonstrates the divergent characteristics of genes based on their CV. High CV genes tend to form co-expression clusters and they explain bivalency at least in part." @default.
• W2274308875 created "2016-06-24" @default.
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• W2274308875 date "2016-08-01" @default.
• W2274308875 modified "2023-10-16" @default.
• W2274308875 title "Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data" @default.
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• W2274308875 doi "https://doi.org/10.1016/j.compbiolchem.2016.02.004" @default.
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