ArticleBMC genomics2017
Mosaic autosomal aneuploidies are detectable from single-cell RNAseq data.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 30 citations in OpenAlex.
- Machine learning-driven decoding of maternal immune signatures in repeated pregnancy loss.PLoS computational biology · 2026Article
- Chromosomal instability in human trophoblast stem cells and placentas.Nature communications · 2025Article
- Exploring and validating the marmoset as a primate model for chromosomal instability in early development.Molecular human reproduction · 2025Article
- Comparative Transcriptomic Analyses Reveal Differences in the Responses of Diploid and Triploid Eastern Oysters to Environmental Stress.Evolutionary applications · 2024Article
- Simple aneuploidy evades p53 surveillance and promotes niche factor-independent growth in human intestinal organoids.Molecular biology of the cell · 2024Article
- Identification and Genome-Wide Gene Expression Perturbation of a Trisomy in Chinese Kale (Plants (Basel, Switzerland) · 2023Article
- Mosaic results after preimplantation genetic testing for aneuploidy may be accompanied by changes in global gene expression.Frontiers in molecular biosciences · 2023Article
- Metabolic and epigenetic dysfunctions underlie the arrest of in vitro fertilized human embryos in a senescent-like state.PLoS biology · 2022Article
- Molecular contribution to embryonic aneuploidy and karyotypic complexity in initial cleavage divisions of mammalian development.Development (Cambridge, England) · 2022Article
- The impact of maternal age on gene expression during the GV to MII transition in euploid human oocytes.Human reproduction (Oxford, England) · 2021Article
- SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data.BMC genomics · 2021Article
- Frequent loss of heterozygosity in CRISPR-Cas9-edited early human embryos.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Depletion of aneuploid cells in human embryos and gastruloids.Nature cell biology · 2021Article
- Single-cell analysis of human embryos reveals diverse patterns of aneuploidy and mosaicism.Genome research · 2020Article
- Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data.Genes · 2020Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundAneuploidies are copy number variants that affect entire chromosomes. They are seen commonly in cancer, embryonic stem cells, human embryos, and in various trisomic diseases. Aneuploidies frequently affect only a subset of cells in a sample; this is known as "mosaic" aneuploidy. A cell that harbours an aneuploidy exhibits disrupted gene expression patterns which can alter its behaviour. However, detection of aneuploidies using conventional single-cell DNA-sequencing protocols is slow and expensive.
methodsWe have developed a method that uses chromosome-wide expression imbalances to identify aneuploidies from single-cell RNA-seq data. The method provides quantitative aneuploidy calls, and is integrated into an R software package available on GitHub and as an Additional file of this manuscript.
resultsWe validate our approach using data with known copy number, identifying the vast majority of aneuploidies with a low rate of false discovery. We show further support for the method's efficacy by exploiting allele-specific gene expression levels, and differential expression analyses.
conclusionsThe method is quick and easy to apply, straightforward to interpret, and represents a substantial cost saving compared to single-cell genome sequencing techniques. However, the method is less well suited to data where gene expression is highly variable. The results obtained from the method can be used to investigate the consequences of aneuploidy itself, or to exclude aneuploidy-affected expression values from conventional scRNA-seq data analysis.
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