Gina Vong

The Perfect Sunrise: The effect of morning light on disease resistance in greenhouse crops

About me

My interest in plants grew during my undergraduate at Durham University. Here, I learnt about their importance to human society. During summer internships, I became fascinated with the intricate mechanisms that plants have evolved for processing information. My PhD project investigates how plants process and integrate signals / information from multiple environmental sources, touching on several branches of plant biology.


Outside the lab, I am a musician and organist – if I’m not in the lab, you’ll probably find me in a church organ loft! I occasionally dabble with visual arts and strongly believe that the arts improve my abilities as a scientist and vice versa.


I am also passionate about improving the accessibility of science through systemic and structural means. Everyone should be able to consume and participate in scientific progress.


My Project

A global $60 billion is estimated to be lost annually through fungal crop damage and its management, with these losses projected to increase with climate change. Therefore, understanding the mechanisms behind plant-pathogen interactions may help reduce crop damage and provide for the global population.


Plants have greater disease resistance in the morning. This is regulated through plants’ circadian clock. In addition, recent research has revealed a transcriptional Dawn Burst Network that plants exhibit in response to early morning light. The hub genes from this network have been implicated in resistance to Botrytis cinerea (grey mould disease), suggesting that morning light may also play a role in plants’ morning disease resistance.


My project further investigates this connection between morning light and disease dynamics. By experimenting on both Arabidopsis (the lab rat of plant science) and lettuce, we hope to see whether these networks and disease dynamics are common across plant species (crops in particular). The project will use a combination of wet-lab phenotyping and transcriptomics experiments along with computational approaches to get a well-rounded understanding of morning disease resistance in plants. 



Twitter: @ClarinetCadenza