Linking single-cell biology and genetic variation

Genetic variation between people can affect molecular traits such as gene expression levels in many ways. Classical analysis approaches have predominantly considered mean abundance changes, where genetic variants are correlated with difference in mean expression. Thanks to recent advances in single-cell technologies it is now possible able to assays the whole transcriptome of hundreds of single-cells drawn from a cell population. These data enable to derive extremely rich molecular phenotypes, including cell-to-cell variance and dynamical properties of single cells along differentiation trajectories.
In this project, we will leverage existing single-cell transcriptome data from differentiating human iPSCs to understand how individual genetic variants shape single-cell transcriptomes. We will test for allele-specific differences of expression abundance within cells from a single donor as well as changes in expression patterns between donors. This project will provide an excellent introduction into the field of single-cell genomics and genetics.
Within the HipSci consortium (www.hipsci.org) and in the context of collaborations with Sarah Teichmann's lab we are generating single-cell variation data from genetically diverse donors. These data provide the unique opportunity to study the link between genotype and transcriptome heterogeneity. These projects can be interdisciplinary, covering a combination of experimental components, computational single-cell genomics as well as statistical genetics.