Physiology, gene expression, and epiphenotype of two Dianthus broteri polyploid cytotypes under temperature stress.
Javier López-JuradoJesús Picazo-AragonésConchita AlonsoFrancisco BalaoEnrique Mateos-NaranjoPublished in: Journal of experimental botany (2023)
Increasing evidence supports a major role of abiotic stress response in the success of plant polyploids, which usually thrive in harsh environments. However, understanding the ecophysiology of polyploids is challenging due to interactions between genome doubling and natural selection. Here, we investigated physiological responses, gene expression, and the epiphenotype of two related Dianthus broteri cytotypes -with different genome duplications (4× and 12×) and evolutionary trajectories- to short extreme temperature events (42/28 ºC and 9/5 ºC). 12× D. broteri showed higher expression of stress-responsive genes (SWEET1, PP2C16, AI5L3 and ATHB7) and enhanced gas exchange compared to 4×. Under heat stress, both ploidies had largely impaired physiological performance and altered gene expression, with reduced cytosine methylation. However, the 12× cytotype exhibited remarkable physiological tolerance (maintaining gas exchange and water status via greater photochemical integrity and probably enhanced water storage) while downregulating PP2C16 expression. Conversely, 4× D. broteri was susceptible to thermal stress despite prioritising water conservation, showing signs of non-stomatal photosynthetic limitations and irreversible photochemical damage. This cytotype also presented gene-specific expression patterns under heat, upregulating ATHB7. These findings provide insights into divergent stress response strategies and physiological resistance resulting from polyploidy, highlighting its widespread influence on plant function.
Keyphrases
- gene expression
- heat stress
- genome wide
- dna methylation
- poor prognosis
- binding protein
- genome wide identification
- oxidative stress
- climate change
- room temperature
- stress induced
- machine learning
- depressive symptoms
- artificial intelligence
- cell wall
- mass spectrometry
- deep learning
- genome wide analysis
- plant growth
- single molecule