Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression
Open Access
- 10 February 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Communications
- Vol. 11 (1), 1-14
- https://doi.org/10.1038/s41467-020-14457-z
Abstract
Recent developments in stem cell biology have enabled the study of cell fate decisions in early human development that are impossible to study in vivo. However, understanding how development varies across individuals and, in particular, the influence of common genetic variants during this process has not been characterised. Here, we exploit human iPS cell lines from 125 donors, a pooled experimental design, and single-cell RNA-sequencing to study population variation of endoderm differentiation. We identify molecular markers that are predictive of differentiation efficiency of individual lines, and utilise heterogeneity in the genetic background across individuals to map hundreds of expression quantitative trait loci that influence expression dynamically during differentiation and across cellular contexts.Keywords
This publication has 62 references indexed in Scilit:
- STAR: ultrafast universal RNA-seq alignerBioinformatics, 2012
- An integrated encyclopedia of DNA elements in the human genomeNature, 2012
- PeakRanger: A cloud-enabled peak caller for ChIP-seq dataBMC Bioinformatics, 2011
- Reference Maps of Human ES and iPS Cell Variation Enable High-Throughput Characterization of Pluripotent Cell LinesCell, 2011
- Measuring dementia carers' unmet need for services - an exploratory mixed method studyBMC Health Services Research, 2010
- BEDTools: a flexible suite of utilities for comparing genomic featuresBioinformatics, 2010
- Fast and accurate short read alignment with Burrows–Wheeler transformBioinformatics, 2009
- Visualizing Spatiotemporal Dynamics of Multicellular Cell-Cycle ProgressionCell, 2008
- PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage AnalysesAmerican Journal of Human Genetics, 2007
- Statistical significance for genomewide studiesProceedings of the National Academy of Sciences of the United States of America, 2003