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Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity.

Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity. Cell stem cell Carcamo-Orive, I., Hoffman, G. E., Cundiff, P., Beckmann, N. D., D'Souza, S. L., Knowles, J. W., Patel, A., Papatsenko, D., Abbasi, F., Reaven, G. M., Whalen, S., Lee, P., Shahbazi, M., Henrion, M. Y., Zhu, K., Wang, S., Roussos, P., Schadt, E. E., Pandey, G., Chang, R., Quertermous, T., Lemischka, I. 2016

Abstract

Variability in induced pluripotent stem cell (iPSC) lines remains a concern for disease modeling and regenerative medicine. We have used RNA-sequencing analysis and linear mixed models to examine the sources of gene expression variability in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele-specific expression show that iPSCs retain a donor-specific gene expression pattern. Network, pathway, and key driver analyses showed that Polycomb targets contribute significantly to the non-genetic variability seen within and across individuals, highlighting this chromatin regulator as a likely source of reprogramming-based variability. Our findings therefore shed light on variation between iPSC lines and illustrate the potential for our dataset and other similar large-scale analyses to identify underlying drivers relevant to iPSC applications.

View details for DOI 10.1016/j.stem.2016.11.005

View details for PubMedID 28017796