Mapping the effects of genetic variants from genes to cells to disease

Collaborators: Stephen Montgomery & Oliver Stegle


Our laboratories study the molecular consequences of genetic variation. Advances in genome sequencing, functional genomics, cellular phenotyping and population biobanks provide new opportunities to understand the genetic causes of many human diseases. Our groups have recently collaborated to demonstrate how large-scale iPSC transcriptome analysis in human populations can enable interpretation of complex and rare genetic disease risk variants (Bonder, Smail et al, Nature Genetics, 2021). Building on these approaches, we aim to better map causal variants, gene regulatory networks and understand cell-to-cell interactions. 


Utilizing data from the HipSci initiative, the laboratories of Stephen Montgomery (Stanford), Oliver Stegle (EMBL), and Kelly Frazer (UCSD) have collected genetic and genomic data from a diverse range of human iPSC. At present, this resource already spans over 1000 distinct iPSC lines, with detailed molecular data including genomic, proteomic and phenotypic data.  This invaluable database provides a comprehensive source of information for the scientific community to advance iPSC research and drive further discoveries. The team seeks to use this platform to address genetic questions for which iPSC are particularly suited, including rare disease genomics and the genetic regulation of stem cells in general. We are interested in developing new computational approaches for rare variant interpretation using multi-omics data, developing regulatory networks and expanding the use and accessibility of these data for clinical applications.


Bonder, M.J & Smail, C., et al., Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics. Nat Genet (2021).

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