A network-based approach for identifying periodically expressed proteins

  • Thomas Minchington

Student thesis: Phd


Oscillatory genes are genes for which the mRNA, protein or both are expressed periodically and are an emerging area of study across multiple fields, including development, inflammation and cell fate determination. To date, we are only aware of a handful of genes which are expressed in this periodic fashion, especially at the ultradian (shorter than a day) scale. Despite the critical role that oscillatory expression plays in biological processes; from the patterning of embryos to the timing and fate of differentiation in neuronal development, we are only aware of a handful of these oscillatory genes. Moreover, the current methods for identifying oscillations are lacking. Identification of novel oscillatory genes is key to advancing knowledge within the field. Here I integrate transcriptional regulator (TR) binding data and microRNA target data to construct a gene interaction network. Using this network, I identified patterns of interactions, termed "network motifs", which match those of existing synthetic and biological oscillators. I found that oscillatory type motifs were enriched within the network and were highly conserved between tissues in terms of their structure. Surprisingly TRs were found to utilise different microRNAs between tissues to maintain their network motif structure. These results indicated that there might be a high prevalence of oscillators within gene interaction networks. One motif that was highly enriched in the gene interaction network was the incoherent feedback loop (IFBL) motif, an autoregulatory TR, which also has indirect feedback through a microRNA. To investigate the potential of the IFBL motif as a signature for oscillatory genes, I generated endogenous fluorescent knock-in lines. The knock-in lines revealed the potential oscillatory expression of REST, FOXP1 and BCL11A along with long term dynamics in KDM5B. The oscillatory behaviour of REST expression was further validated in clonal lines and was determined to have a period of 8-15 hours in MCF7 cancer cells. Further, preliminary data reveals a potential link between REST dynamics cancer stem-like cells which may reveal new insights into cancer cell type specification. Here I have shown, using a network-based approach, the discovery of the novel oscillatory gene REST in MCF7 cells. This approach also revealed the potential oscillatory expression of FOXP1 and BCL11A. These results indicate that it may be possible to use network structure as a basis for the identification of novel oscillatory genes allowing for the expansion of oscillatory dynamics into new frontiers.
Date of Award1 Aug 2020
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorNancy Papalopulu (Supervisor) & Sam Griffiths-Jones (Supervisor)

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