Poster
Feixue Liao
University of York
York, England, United Kingdom
Juanjuan Wang
University of Cambridge
Cambridge, England, United Kingdom
Amy Briffa
John Innes Centre
Norwich, England, United Kingdom
Luisa Valencia Riascos
University of York
York, England, United Kingdom
Ana Almeida
University of Cambridge
Cambridge, England, United Kingdom
Katherine Denby
University of York
York, England, United Kingdom
richard Morris
John Innes Centre
Norwich, England, United Kingdom
Nicola Patron
University of Cambridge
Cambridge, England, United Kingdom
Lettuce is an economically significant crop, valued at over £200 million in the UK. However, fungal pathogens such as Botrytis cinerea and Sclerotinia sclerotiorum cause 20-30% lettuce yield loss. Current control methods, including fungicides, are unsustainable, and field resistance is increasing. This study aims to enhance lettuce disease resistance by rewiring the gene regulatory network (GRN) involved in its defense response. We developed a GRN model using gene expression datasets to identify transcription factor (TF)-target gene interactions linked to pathogen-induced transcriptional changes. From this, we selected a subnetwork of 18 TFs with positive and negative impacts on lettuce defense. To validate the network, we are using bioinformatics to analyze promoter sequences and experimental methods using lettuce protoplasts for high-throughput validation. These include transient expression of TFs and target gene promoters linked to luminescent reporters and the Transient System for Specific TF Targets (TARGET) assay. This approach activates specific TFs in protoplasts, inhibiting further translation, and profiling with RNA-seq to identify direct downstream targets. By integrating these results, we refine the subnetwork and identify target genes and binding sites for each TF. Simulating this validated network will predict how to rewire it to enhance disease resistance via synthetic TFs, targeted gene promoter editing, or new regulatory elements in target gene promoters.