ArticleComputational biology and chemistry2016
Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data.
Article in Computational biology and chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Self-organization underlies developmental robustness in plants.Cells & development · 2025Review
- A four eigen-phase model of multi-omics unveils new insights into yeast metabolic cycle.NAR genomics and bioinformatics · 2025Article
- Somatosensory neurons express specific sets of lincRNAs, and lincRNA CLAP promotes itch sensation in mice.EMBO reports · 2023Article
- Stochastic expression of invasion genes in Plasmodium falciparum schizonts.Nature communications · 2022Article
- Identification of a ZC3H12D-regulated competing endogenous RNA network for prognosis of lung adenocarcinoma at single-cell level.BMC cancer · 2022Article
- DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data.Nature communications · 2021Article
- A top-down measure of gene-to-gene coordination for analyzing cell-to-cell variability.Scientific reports · 2021Article
- Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships.Frontiers in plant science · 2020Article
- Article
- DoubletDecon: Deconvoluting Doublets from Single-Cell RNA-Sequencing Data.Cell reports · 2019Article
- Paf1c defects challenge the robustness of flower meristem termination inDevelopment (Cambridge, England) · 2019Article
- Differential Variation Analysis Enables Detection of Tumor Heterogeneity Using Single-Cell RNA-Sequencing Data.Cancer research · 2019Article
- Expression dynamics of repetitive DNA in early human embryonic development.BMC genomics · 2019Article
- Single-Cell RNA-Sequencing and Optical Electrophysiology of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes Reveal Discordance Between Cardiac Subtype-Associated Gene Expression Patterns and Electrophysiological Phenotypes.Stem cells and development · 2019Article
- Transcriptomics of Arabidopsis sperm cells at single-cell resolution.Plant reproduction · 2019Article
- Widespread inter-individual gene expression variability inMolecular systems biology · 2019Article
- Single-cell systems biology: probing the basic unit of information flow.Current opinion in systems biology · 2018Article
- Delineating biological and technical variance in single cell expression data.The international journal of biochemistry & cell biology · 2017Review
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundGene 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.
methodsWe 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.
resultsHighly 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.
conclusionsTaken 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.
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