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

Anna Cuomo(European Bioinformatics Institute), Daniel D. Seaton(European Bioinformatics Institute), Davis J. McCarthy(European Bioinformatics Institute), Iker Martinez(Wellcome Sanger Institute), Marc Jan Bonder(European Bioinformatics Institute), José Garcia‐Bernardo(Wellcome Sanger Institute), Shradha Amatya(Wellcome Sanger Institute), Pedro Madrigal(Ames Research Center), Abigail Isaacson(Wellcome Sanger Institute), Florian Buettner(European Bioinformatics Institute), Andrew Knights(Wellcome Sanger Institute), Kedar Nath Natarajan(University of Southern Denmark), Chukwuma A. Agu(Wellcome Sanger Institute), Alex Alderton(Wellcome Sanger Institute), Petr Danecek(Wellcome Sanger Institute), Rachel Denton(Wellcome Sanger Institute), Richard Durbin(Wellcome Sanger Institute), Daniel J. Gaffney(Wellcome Sanger Institute), Ângela Gonçalves(Wellcome Sanger Institute), Reena Halai(Wellcome Sanger Institute), Sarah Harper(Wellcome Sanger Institute), Christopher M. Kirton(Wellcome Sanger Institute), Anja Kolb‐Kokocinski(Wellcome Sanger Institute), Andreas Leha(Wellcome Sanger Institute), Shane McCarthy(Wellcome Sanger Institute), Yasin Memari(Wellcome Sanger Institute), Minal Patel(Wellcome Sanger Institute), Ewan Birney(European Bioinformatics Institute), Francesco Paolo Casale(European Bioinformatics Institute), Laura Clarke(European Bioinformatics Institute), Peter W. Harrison(European Bioinformatics Institute), Helena Kilpinen(European Bioinformatics Institute), Ian Streeter(European Bioinformatics Institute), Davide Denovi(King's College London), Ruta Meleckyte(King's College London), Natalie Moens(King's College London), Fiona M. Watt(King's College London), Willem H. Ouwehand(National Health Service), Angus I. Lamond(University of Dundee), Dalila Bensaddek(University of Dundee), Philip L. Beales(University College London), Ludovic Vallier(Wellcome/MRC Cambridge Stem Cell Institute), John C. Marioni(European Bioinformatics Institute), Mariya Chhatriwala(Wellcome Sanger Institute), Oliver Stegle(European Bioinformatics Institute)
Nature Communications
February 10, 2020
10.1038/s41467-020-14457-z
Cited by 363Open Access
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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.

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