ArticleGenome biology2015
Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation.
Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.
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Who cites it
52 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transcriptional signatures of brain aging and Alzheimer's disease: What are our rodent models telling us?Behavioural brain research · 2017Pooled it
- Unraveling the Molecular Mechanism of Bider Marking Formation in Dun Mongolian Horses Through Transcriptome Sequencing.Animals : an open access journal from MDPI · 2026Article
- Comparative analysis of RT-qPCR, flow cytometry, and Di-4-ANEPPDHQ fluorescence for distinguishing macrophages phenotypes.Biochemistry and biophysics reports · 2025Article
- NEK2 is a potential pan-cancer biomarker and immunotherapy target.Discover oncology · 2024Article
- Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging.Genome biology · 2023Article
- Transcriptional profiling of dental sensory and proprioceptive trigeminal neurons using single-cell RNA sequencing.International journal of oral science · 2023Article
- Integrative genetic and single cell RNA sequencing analysis provides new clues to the amyotrophic lateral sclerosis neurodegeneration.Frontiers in neuroscience · 2023Article
- Cre driver mouse lines for thalamocortical circuit mapping.The Journal of comparative neurology · 2022Article
- SkewC: Identifying cells with skewed gene body coverage in single-cell RNA sequencing data.iScience · 2022Article
- Pan-Cancer Analysis on the Oncogenic Role of Programmed Cell Death 10.Journal of oncology · 2022Article
- Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer.Communications biology · 2021Article
- Multi-omics integration in the age of million single-cell data.Nature reviews. Nephrology · 2021Review
- A bioinformatic study revealed serotonergic neurons are involved in the etiology and therapygenetics of anxiety disorders.Translational psychiatry · 2021Article
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- Lamin B2 Levels Regulate Polyploidization of Cardiomyocyte Nuclei and Myocardial Regeneration.Developmental cell · 2020Article
- Zebrafish heart regeneration: Factors that stimulate cardiomyocyte proliferation.Seminars in cell & developmental biology · 2020Review
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- The basis of cellular and regional vulnerability in Alzheimer's disease.Acta neuropathologica · 2019Review
- Control of cytokinesis by β-adrenergic receptors indicates an approach for regulating cardiomyocyte endowment.Science translational medicine · 2019Article
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13 authors.
Funding
Abstract
backgroundDifferentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question.
resultsWe present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved.
conclusionsSingle-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.
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