BBSRC EASTBIO DTP - Gene regulation in the development of mechanosensory cells of the inner ear: bioinformatic and experimental analysis in a stem cell model

Sensory hair cells (HCs) of the inner ear are remarkable mechanoreceptors that convert auditory stimuli into electrical signals. Hearing impairments are usually caused by damage and death of these sensory HCs. There is no capacity to replace lost HCs in the mammalian inner ear, and so HC loss through disease, drugs with ototoxic side effects, loud noise, or simply through aging, leads to permanent hearing deficits for millions of people worldwide. Advancement towards a therapeutic solutions include stimulating the inner ear to regenerate HCs, but this requires a deeper understanding of the genetic networks involved in HC generation during embryonic ear development. The bHLH transcription factor, Atoh1, controls HC generation in the embryo (Bermingham et al., 1999). But the genetic network in which it participates, including its downstream target genes and its interactions with other otic transcription factors, is poorly known. In this project the student will make use of data generated from a novel method to generate mouse embryonic stem cell-derived HCs in culture (Costa et al., 2015). This approach is relies on using mESCs engineered with a Dox-inducible transgene expressing Atoh1 along with two other transcription factors known to be important for hair cell differentiation (Gfi1 and Pou4f3). This allows for the first time the application of genome-wide methods for detecting target genes during HC differentiation – including ChIP-seq and RNA-seq methods. Dr Aida Costa, the lead author of the new protocol, is currently a post-doctoral researcher in the Jarman lab generating such datasets. The student on this project will work closely with Dr Costa to apply computational analysis to the large amounts of data being generated, with the aim of discovering the target genes that are activated by the HC transcription factors during induction of HC differentiation and using computational modelling to build genetic network models of the HC differentiation. The student will then have the opportunity for wet lab experiments (using the ES cell system) to test predictions that arise from the computer analysis and modelling. This project would suit either a biologist or a computational scientist who wishes to receive cross-disciplinary training, provided by the two supervisors with complementary expertise. Training would be provided in computational handling of large next generation sequencing (NGS) datasets, their bioinformatic interrogation, and computer modelling of gene networks. Wet-lab training would involve embryonic stem cell culture and gene expression analysis in stem cell-derived HCs.