A village in a dish model system for population-scale hiPSC studies

Abstract The mechanisms by which DNA alleles contribute to disease risk, drug response, and other human phenotypes are highly context-specific, varying across cell types and different conditions. Human induced pluripotent stem cells are uniquely suited to study these context-dependent effects but ce...

Full description

Bibliographic Details
Published in:Nature Communications
Main Authors: Drew R. Neavin, Angela M. Steinmann, Nona Farbehi, Han Sheng Chiu, Maciej S. Daniszewski, Himanshi Arora, Yasmin Bermudez, Cátia Moutinho, Chia-Ling Chan, Monique Bax, Mubarika Tyebally, Vikkitharan Gnanasambandapillai, Chuan E. Lam, Uyen Nguyen, Damián Hernández, Grace E. Lidgerwood, Robert M. Graham, Alex W. Hewitt, Alice Pébay, Nathan J. Palpant, Joseph E. Powell
Format: Article
Language:English
Published: Nature Portfolio 2023-06-01
Online Access:https://doi.org/10.1038/s41467-023-38704-1
Description
Summary:Abstract The mechanisms by which DNA alleles contribute to disease risk, drug response, and other human phenotypes are highly context-specific, varying across cell types and different conditions. Human induced pluripotent stem cells are uniquely suited to study these context-dependent effects but cell lines from hundreds or thousands of individuals are required. Village cultures, where multiple induced pluripotent stem lines are cultured and differentiated in a single dish, provide an elegant solution for scaling induced pluripotent stem experiments to the necessary sample sizes required for population-scale studies. Here, we show the utility of village models, demonstrating how cells can be assigned to an induced pluripotent stem line using single-cell sequencing and illustrating that the genetic, epigenetic or induced pluripotent stem line-specific effects explain a large percentage of gene expression variation for many genes. We demonstrate that village methods can effectively detect induced pluripotent stem line-specific effects, including sensitive dynamics of cell states.
ISSN:2041-1723