Village in a dish: a model system for population-scale hiPSC studies
preprint
OA: closed
CC-BY-NC-4.0
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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- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-NC-4.0