Developing new therapies hinges on our ability to understand the cellular mechanisms that underlie diseases. Stem cells are a powerful tool for disease modelling, and in particular induced pluripotent stem cells (iPSC) are increasingly used to study the functional effects of human disease alleles. The Kilpinen group is interested in cellular genetics, i.e. how genetic variants, common or rare, affect cellular phenotypes. We combine experimental and computational methods in genomics to study the transcriptomes, epigenomes, and cell-level phenotypes in iPSC-based models.
Some of our current projects include:
1. Characterisation of iPSCs derived from a large cohort of rare human diseases
The ability to accurately analyse molecular data from stem-cell-based disease models is key for advancing translational research of rare diseases. However, it is currently not known whether stem cells derived from individuals carrying severe disease mutations are molecularly different from those from healthy individuals. In this project, we build on our past work in the Human Induced Pluripotent Stem Cell Initiative (Kilpinen et al. 2017 Nature) to study transcriptomic differences among the largest available collection of iPSCs from 210 individuals with a rare genetic disease.
2. Genetic background effects in iPSC-based models
The genetic background of donor individuals has been shown to have an effect on molecular phenotypes measured from iPSCs (Kilpinen et al. 2017 Nature). However, the benefit of using patient-derived iPSCs instead of engineering the variant-of-interest into an iPSC line derived from a healthy individual has not been comprehensively evaluated. In this project, we use CRISPR-Cas9 technology to study the cellular effects of specific rare disease mutations in different genetic backgrounds by comparing patient-derived neuronal cells to wild-type cells and cells with engineered mutations.
3. Effects of loss-of-function mutations in epigenetic modifiers on neuronal development
Developmental disorders are frequently caused by rare, loss-of-function mutations in genes that encode for different components of the epigenetic machinery of the cell. This project aims to identify and validate therapeutic targets for neurodevelopmental and psychiatric disorders with a known genetic basis, by comparing transcriptomic profiles of disease states to the response profiles of drugs and gene knockouts. Specifically, we study how different neuronal cell types derived from human iPS cells are affected by these disease-causing mutations. We use a combination of patient-derived and CRISPR-engineered cell lines and profile neuronal differentiation over time using single-cell transcriptomics. This work is a collaboration with Prof. Matthew Hurles (WSI), Dr. Emmanouil Metzakopian (UKDRI) and Takeda, and is funded by Open Targets.
4. Improved detection of allele-specific expression using personalised calling
Allele-specific expression (ASE) is the imbalanced expression of the two alleles of a gene. While most genes are expressed equally from both alleles, gene regulatory differences driven by genetic changes (i.e. regulatory variants) frequently cause the two alleles to be expressed at different levels, resulting in allele-specific expression patterns. The power of ASE analysis lies in its applicability to individual samples. We are developing a personalised ASE calling pipeline that combines diploid genome mapping with other features that improve the accuracy of ASE calls in single-samples analyses. This work is a collaboration with Dr. Alan Hodgkinson (KCL).