Village in a dish: a model system for population-scale hiPSC studies
Drew R. NeaviniD, Angela M. Steinmann, Nona FarbehiiD, Han Sheng ChiuiD, Maciej DaniszewskiiD, Himanshi Arora, Yasmin Bermudez, Cátia MoutinhoiD, Chia‐Ling ChaniD, Monique BaxiD, Mubarika TyeballyiD, Vikkitharan GnanasambandapillaiiD, Chuan En Lam, Uyen T. T. NguyeniD, Damián HernándeziD, Grace E. LidgerwoodiD, Robert M. GrahamiD, Alex William HewittiD, Alice PébayiD, Nathan J. PalpantiD, Joseph E. PowelliD
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 under different conditions. Human induced pluripotent stem cells (hiPSCs) are uniquely suited to study these context-dependent effects, but to do so requires cell lines from hundreds or potentially thousands of individuals. Village cultures, where multiple hiPSC lines are cultured and differentiated together in a single dish, provide an elegant solution for scaling hiPSC 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 back to a donor line using single cell sequencing, and addressing whether line-specific signaling alters the transcriptional profiles of companion lines in a village culture. We generated single cell RNA sequence data from hiPSC lines cultured independently (uni-culture) and in villages at three independent sites. We show that the transcriptional profiles of hiPSC lines are highly consistent between uni- and village cultures for both fresh (0.46 < R < 0.88) and cryopreserved samples (0.46 < R < 0.62). Using a mixed linear model framework, we estimate that the proportion of transcriptional variation across cells is predominantly due to donor effects, with minimal evidence of variation due to culturing in a village system. We demonstrate that the genetic, epigenetic or hiPSC line-specific effects on gene expression are consistent whether the lines are uni- or village-cultured (0.82 < R < 0.94). Finally, we identify the consistency in the landscape of cell states between uni- and village-culture systems. Collectively, we demonstrate that village methods can be effectively used to detect hiPSC line-specific effects including sensitive dynamics of cell states.
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