Abstract

Decomposing the Sources of Molecular Variation in Human Induced Pluripotent Stem Cells

Oliver Stegle, Research Group Leader, EMBL-European Bioinformatics Institute (EMBL-EBI)

Induced pluripotent stem cells (iPSC) are increasingly used to model functional effects of human disease alleles. The Human Induced Pluripotent Stem Cells Initiative (www.hipsci.org) is generating a reference panel of iPSC lines together with rich multi-omics phenotype data from 500 healthy individuals and 500 individuals with selected rare disorders, which will be made available to the research community and industry. To date, HIPSCI has generated and phenotyped 640 high quality iPSC lines from 220 individuals enabling a comprehensive survey of the sources of variation and heterogeneity in IPSCs. Here, we describe the initial analysis of the genomes, epigenomes, transcriptomes and proteomes of IPS lines from healthy individuals generated by HIPSCI. Despite an extensive literature on genetic and epigenetic heterogeneity in IPSCs, the lines we have generated are remarkably genetically and epigenetically stable. We use a variance component approach to decompose the sources of molecular variation between lines, finding that genetic effects can be reliably detected across a range of molecular and cellular assays, and often explain substantially greater variation than many other technical and biological factors, including cell culture conditions, donor gender, age and tissue of origin. We study a first map of expression quantitative trait loci in iPSCs and connect these with data from other somatic tissues and disease-associated variants. Notably, we also identify genetic variants that affect the heterogeneity between replicate lines, which can in part be explained by interactions (GxE) with known cellular environment (growth media) and state (pluripotency). Finally, we examine how genetic and non-genetic factors influence key IPS cell properties such as cell growth rates and differentiation ability. We anticipate that both the lines and data generated by HIPSCI will form an invaluable resource for the future study of human disease and development.