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

Area of Science:

• Genomics and Stem Cell Biology
• Systems Biology and Bioinformatics

Background:

• Understanding how DNA variations influence human traits like disease risk and drug response requires studying context-specific effects across diverse cell types and conditions.
• Human induced pluripotent stem cells (hiPSCs) are valuable tools for investigating these context-dependent effects, but require large numbers of individual cell lines for population-scale studies.

Purpose of the Study:

• To introduce and validate the utility of 'village models' for scaling up experiments using hiPSCs to population-level sample sizes.
• To demonstrate a method for assigning individual cells to their respective hiPSC lines within a village culture using single-cell sequencing.
• To analyze the contributions of genetic, epigenetic, and hiPSC-specific factors to gene expression variation.

Main Methods:

• Development and application of 'village culture' systems, co-culturing multiple hiPSC lines in a single experimental setting.
• Utilizing single-cell sequencing technology to accurately assign individual cells back to their originating hiPSC line.
• Computational analysis to quantify the proportion of gene expression variation attributable to genetic, epigenetic, and hiPSC line-specific effects.

Main Results:

• Successfully demonstrated the feasibility of assigning cells to specific hiPSC lines within village cultures using single-cell sequencing.
• Showed that genetic, epigenetic, and hiPSC line-specific factors collectively explain a significant percentage of gene expression variability across many genes.
• Confirmed that village methods effectively detect hiPSC line-specific effects, including dynamic changes in cell states.

Conclusions:

• Village models offer an efficient and scalable approach for population-scale studies using hiPSCs, overcoming previous limitations in sample size.
• The methodology allows for precise cell-lineage tracing and facilitates the dissection of complex gene expression regulation.
• This approach is powerful for identifying context-dependent genetic and epigenetic influences on human phenotypes.