Tesi etd-11262024-114929
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Tipo di tesi
Dottorato
Autore
CASTELLANA, SIMONE
URN
etd-11262024-114929
Titolo
Environmental genome-wide association studies across precipitation regimens reveal that the E3 ubiquitin ligase MBR1 regulates plant adaptation to rainy environments
Settore scientifico disciplinare
AGR/07
Corso di studi
Istituto di Scienze della Vita - PH.D. IN AGROBIODIVERSITY
Commissione
relatore Prof. PERATA, PIERDOMENICO
Parole chiave
- Environmental Genome Wide Association Analyses
Data inizio appello
21/01/2025;
Disponibilità
completa
Riassunto analitico
In an era characterized by rapidly changing and less-predictable weather conditions fueled by the climate crisis, understanding the mechanisms underlying local adaptation in plants is of paramount importance for the conservation of species. As the frequency and intensity of extreme precipitation events increase, so are the flooding events resulting from soil water saturation. The deriving onset of hypoxic stress is one of the leading causes of crop damage and yield loss. By combining genomics and remote sensing data, today it is possible to probe natural plant populations that have evolved in different rainfall regimes and look for molecular adaptation to hypoxia. Here, using an environmental genome-wide association study (eGWAS) on 934 non-redundant georeferenced Arabidopsis ecotypes, we have identified functional variants for the gene MED25 BINDING RING-H2 PROTEIN 1 (MBR1). This is a ubiquitin-protein ligase that regulates MEDIATOR25 (MED25), part of a multiprotein complex that interacts with transcription factors which act as key drivers of the hypoxic response in Arabidopsis, namely the RELATED TO AP2 proteins, RAP2.2 and RAP2.12. Through experimental validation, we show that natural variants of MBR1 have a differential impact on the stability of MED25 and, in turn, on hypoxia tolerance. This study also highlights the pivotal role of the MBR1/MED25 module in establishing a comprehensive hypoxic response. Our findings show that molecular candidates for plant environmental adaptation can be effectively mined from large datasets. This thus supports the need for the integration of forward and reverse genetics with robust molecular physiology validation of the outcomes.
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