Using human induced pluripotent stem cells to identify genetic variants that influence cellular differentiation

Student thesis: Doctoral ThesisDoctor of Philosophy


Quantitative analysis of human induced pluripotent stem cells (iPSCs) from healthy donors is a powerful tool for uncovering the relationship between genetic variants and cellular behaviour. The Human Induced Pluripotent Stem Cell Initiative was established to create a large, high-quality reference panel of iPSCs with accompanying genetic, proteomic and phenotypic data. Using this resource, we have previously combined cell-based assays, high-content imaging and genome sequencing datasets to identify rare, deleterious non-synonymous single nucleotide variants (nsSNVs) that are associated with outlier iPSC phenotypes in the pluripotent state. Based on this evidence, I hypothesise that the presence of rare, deleterious nsSNVs in iPSC lines from different healthy donors can influence their differentiation phenotypes. To test whether nsSNVs influence differentiation, I generated reproducible micropatterned colonies of iPSCs that differentiated to form radially ordered germ layers and could be examined by high-throughput imaging. I custom-built an automated image analysis pipeline that quantifies protein expression and characterises the spatial patterning of germ layer fates. Using this platform, I characterised the differentiation phenotypes of 13 iPSC lines from 9 healthy donors that harbour rare and deleterious nsSNVs in genes related to cell adhesion or germ layer development. All iPSC lines tested could differentiate into the three germ layers; however, there was donor-specific variation in the germ layer patterning. I identified one iPSC line that harbours rare, deleterious nsSNVs in ITGB1 and TBXT, which presented an outlier phenotype of expanded endodermal differentiation. This phenotype could be partially reproduced in other cell lines by disturbing integrin-mediated adhesion with function-blocking antibodies. This study thus establishes a platform for investigating the impact of nsSNVs on differentiation. This could improve the phenotypic characterisation of human iPSC biobanks and could provide a greater insight into the genetic contribution to variability in iPSC phenotypes.
Date of Award1 Sept 2021
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorFiona Watt (Supervisor) & Ivo Lieberam (Supervisor)

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