Biased Allelic Expression in Human Primary Fibroblast Single Cells
Open accessAbstract
The study of gene expression in mammalian single cells via genomic technologies now provides the possibility to investigate the patterns of allelic gene expression. We used single-cell RNA sequencing to detect the allele-specific mRNA level in 203 single human primary fibroblasts over 133,633 unique heterozygous single-nucleotide variants (hetSNVs). We observed that at the snapshot of analyses, each cell contained mostly transcripts from one allele from the majority of genes; indeed, 76.4% of the hetSNVs displayed stochastic monoallelic expression in single cells. Remarkably, adjacent hetSNVs exhibited a haplotype-consistent allelic ratio; in contrast, distant sites located in two different genes were independent of the haplotype structure. Moreover, the allele-specific expression in single cells correlated with the abundance of the cellular transcript. We observed that genes expressing both alleles in the majority of the single cells at a given time point were rare and enriched with highly expressed genes. The relative abundance of each allele in a cell was controlled by some regulatory mechanisms given that we observed related single-cell allelic profiles according to genes. Overall, these results have direct implications in cellular phenotypic variability.
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Single cell experiments are ideally suited to study gene regulatory noise and robustness.
“Single cell experiments are ideally suited to study gene regulatory noise and robustness3233.”
From Batch effects and the effective design of single-cell gene expression studies (2017) · cites this paper as [32]
Similar monoallelic expression behaviour has been observed in primary human fibroblasts.
“Similar behaviour has been observed in primary human fibroblasts (Borel et al, 2015), suggesting that stochastic monoallelic expression is common across many species and cell types.”
From Using single-cell genomics to understand developmental processes and cell fate decisions (2018) · cites this paper as Borel et al, 2015
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- Authors
- Borel, C., Ferreira, P. G., Santoni, F., Delaneau, O., Fort, A., Popadin, K. Y., Garieri, M., Falconnet, E., Ribaux, P., Guipponi, M., Padioleau, I., Carninci, P., Dermitzakis, E. T., & Antonarakis, S. E.
- Affiliations
- University of Geneva (CH)
- RIKEN (JP)
- Corresponding author
- Dermitzakis, Emmanouil T.
- Antonarakis, Stylianos E.
- ORCID
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 96
- Issue
- 1
- Pages
- 70-80
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC4289680
- OpenAlex
- W1982998729
- Cited by
- 120
- References
- 49
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 3 · 2023: 6 · 2022: 7 · 2021: 9 · 2020: 15 · 2019: 12 · 2018: 11 · 2017: 18 · 2016: 17 · 2015: 10 · 2014: 1
- FWCI
- 6.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Archive ouverte UNIGE (University of Geneva) (publishedVersion)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Funders
- Louis-Jeantet Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (249968, 144082)
- Hôpitaux Universitaires de Genève
- Nature
- Institute of Genetics and Genomics of Geneva
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- allelic expression, monoallelic expression, allele-specific expression, single-cell RNA sequencing, gene expression variation
- MeSH terms
- Alleles, Fibroblasts, Haplotypes, Heterozygote, Humans, Phenotype, RNA, Messenger, Genome, Human, Sequence Analysis, RNA, DNA, Complementary, Single-Cell Analysis
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