@article{bibcite_7416,
  keywords = {Cell Differentiation, Dopaminergic Neurons, Genetic Predisposition to Disease, Humans, induced pluripotent stem cells, Neurogenesis, Oxidative Stress, Quantitative Trait Loci, Receptor, Fibroblast Growth Factor, Type 1, Rotenone, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome},
  author = {Julie Jerber and Daniel D. Seaton and Anna S. E. Cuomo and Natsuhiko Kumasaka and James Haldane and Juliette Steer and Minal Patel and Daniel Pearce and Malin Andersson and Marc Jan Bonder and Ed Mountjoy and Maya Ghoussaini and Madeline A. Lancaster and HipSci Consortium and John C. Marioni and Florian T. Merkle and Daniel J. Gaffney and Oliver Stegle},
  title = {Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation},
  abstract = {Studying the function of common genetic variants in primary human tissues and during development is challenging. To address this, we use an efficient multiplexing strategy to differentiate 215 human induced pluripotent stem cell (iPSC) lines toward a midbrain neural fate, including dopaminergic neurons, and use single-cell RNA sequencing (scRNA-seq) to profile over 1 million cells across three differentiation time points. The proportion of neurons produced by each cell line is highly reproducible and is predictable by robust molecular markers expressed in pluripotent cells. Expression quantitative trait loci (eQTL) were characterized at different stages of neuronal development and in response to rotenone-induced oxidative stress. Of these, 1,284 eQTL colocalize with known neurological trait risk loci, and 46\% are not found in the Genotype-Tissue Expression (GTEx) catalog. Our study illustrates how coupling scRNA-seq with long-term iPSC differentiation enables mechanistic studies of human trait-associated genetic variants in otherwise inaccessible cell states.},
  year = {2021},
  journal = {Nature Genetics},
  volume = {53},
  pages = {304-312},
  month = {2021-03},
  issn = {1546-1718},
  doi = {10.1038/s41588-021-00801-6},
  language = {eng},
}