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Epigenetics: you are what your mother smelled

Principal Supervisor: Dr Andre Pires da Silva 

Secondary Supervisor(s): Professor Jose Gutierrez-Marcos

University of Registration: University of Warwick

BBSRC Research Themes:

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Deadline: 23 May, 2024


Project Outline

Recent evidence suggests that environmental signals received by somatic tissues can influence the phenotype of subsequent generations by reprogramming the germline. For example, trauma experienced by the parental generation causes the transmission of psychiatric diseases. The transmission of symptoms seems to be partially caused by changes in gene activity in the gametes of the parents. However, little is known about how it occurs. We will use a simple model system in which environmental signals (pheromones) sensed by sensory neurons are relayed to the germline to make different kinds of offspring. This model, a nematode named Auanema freiburgensis, provides an easy readout for environmental effects in subsequent generations. We will use state-of-the-art genome engineering techniques and bioinformatics tools to map the cells and signalling systems in somatic and germline cells mediating the transmission of neuronal signalling into the next generation. The results of this research will enhance our understanding of how an individual’s experience can impact the health of descendants.

References

Perez, M.F., and Lehner, B. (2019). Intergenerational and transgenerational epigenetic inheritance in animals. Nature Cell Biology 21, 143-151.

Robles, P., Turner, A., Zuco, G., Adams, S., Paganopolou, P., Winton, M., Hill, B., Kache, V., Bateson, C., and Pires-daSilva, A. (2021). Parental energy-sensing pathways control intergenerational offspring sex determination in the nematode Auanema freiburgensis. BMC Biology 19, 102.

Techniques

  • gene editing tools to generated mutant nematodes (e.g., CRISPR/Cas9)
  • generation of transgenic nematodes (e.g., tagging of specific proteins with fluorescent markers)
  • microscopy (e.g., time lapse videos, confocal microscopy)
  • bioinformatics (e.g., writing scripts in Unix, R and Python)
  • mathematical modelling (R, Python)