Discovering epigenomic landscapes of human brain development to explain later life risk of schizophrenia

Our project answers two inter-linked critical questions for schizophrenia. Firstly, recent genome-wide association studies (GWAS) demonstrate many risk loci but genetic variants lie outside coding regions leaving the problem of which genes account for risk. Secondly, susceptibility to schizophrenia tracks to neurodevelopment but very little of this process is known in human embryos. We have recently compiled the first ever transcriptomic atlas of human organogenesis to discover the precise gene expression signature that specifies the human embryonic brain by contrast to all other systems. These unique, highly privileged data point to single genes within broad schizophrenia risk loci. Moreover, having deciphered the genomic regulatory landscape elsewhere (e.g. active and repressed enhancers), we are poised to embark on the embryonic brain; in other disorders GWAS variants commonly lie in regulatory elements.

Hypothesis: The genes underlying schizophrenia can be pinpointed by determining the transcriptomic and genomic landscape that regulates human embryonic brain development.

Objectives:
1. To map schizophrenia GWAS variants to our transcriptomic atlas of human embryonic brain development.
2. To generate the first regulome of human embryonic brain development comprising active and repressed enhancers and overlay this with GWAS variant data.
3. To integrate the above datasets bioinformatically to correlate regulatory elements with their target genes.
4. To undertake proof-of-principle characterization and functional experiments in model systems to demonstrate causality.

The project will provide highly distinctive training in human embryology, next generation sequencing technologies (e.g. RNA-seq / ChIP-seq), bioinformatics, genomics, model organism studies and molecular psychiatry.

The applicant and team will generate the first ever comprehensive atlas of human embryonic brain development which will be an enormous advance for the research community. Moreover, we expect to make a major contribution to translating genetic risk variants into functional mechanistic significance for one of the most disabling psychiatric disorders.

Jake will be trained in a wide range of research skills including bioinformatics, programming in R and developing new methods of analysis. Furthermore, applying this to psychiatry brings marked interdisciplinarity while an ability to assess function with in vivo models extends training opportunities into whole organ/organism physiology.