Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression

Anna S. E. Cuomo, Daniel D. Seaton, Davis J. McCarthy, Iker Martinez, Marc Jan Bonder, Jose Garcia-Bernardo, Shradha Amatya, Pedro Madrigal, Abigail Isaacson, Florian Buettner, Andrew Knights, Kedar Nath Natarajan, Ludovic Vallier (), John C. Marioni (), Mariya Chhatriwala () and Oliver Stegle ()
Additional contact information
Anna S. E. Cuomo: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton
Daniel D. Seaton: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton
Davis J. McCarthy: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton
Iker Martinez: Wellcome Genome Campus
Marc Jan Bonder: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton
Jose Garcia-Bernardo: Wellcome Genome Campus
Shradha Amatya: Wellcome Genome Campus
Pedro Madrigal: Wellcome Genome Campus
Abigail Isaacson: Wellcome Genome Campus
Florian Buettner: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton
Andrew Knights: Wellcome Genome Campus
Kedar Nath Natarajan: Wellcome Genome Campus
Ludovic Vallier: Wellcome Genome Campus
John C. Marioni: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton
Mariya Chhatriwala: Wellcome Genome Campus
Oliver Stegle: European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton

Nature Communications, 2020, vol. 11, issue 1, 1-14

Abstract: 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.

Date: 2020
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DOI: 10.1038/s41467-020-14457-z

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