TY - JOUR
KW - Cell Differentiation
KW - Cell Line
KW - Endoderm
KW - Female
KW - Gene expression
KW - Gene Expression Profiling
KW - Gene-Environment Interaction
KW - Genetic Association Studies
KW - Genetic Heterogeneity
KW - Humans
KW - induced pluripotent stem cells
KW - Male
KW - Quantitative Trait Loci
KW - Single-Cell Analysis
AU - Anna S. E. Cuomo
AU - Daniel D. Seaton
AU - Davis J. McCarthy
AU - Iker Martinez
AU - Marc Jan Bonder
AU - Jose Garcia-Bernardo
AU - Shradha Amatya
AU - Pedro Madrigal
AU - Abigail Isaacson
AU - Florian Buettner
AU - Andrew Knights
AU - Kedar Nath Natarajan
AU - HipSci Consortium
AU - Ludovic Vallier
AU - John C. Marioni
AU - Mariya Chhatriwala
AU - Oliver Stegle
AB - 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.
BT - Nature Communications
DA - 2020-02-10
DO - 10.1038/s41467-020-14457-z
IS - 1
LA - eng
N2 - 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.
PY - 2020
EP - 810
T2 - Nature Communications
TI - Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression
VL - 11
SN - 2041-1723
ER -