University of Cambridge > Talks.cam > Plant Sciences Research Seminars > Artificial evolution of the resistance gene, Rx, to enhance activation sensitivity in a broad recognition background

Artificial evolution of the resistance gene, Rx, to enhance activation sensitivity in a broad recognition background

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Suzy Stoodley.

Plant Resistance® genes provide protection against a diverse range of pathogens, from nematodes to viruses, with the vast majority encoding proteins from the nucleotide binding leucine-rich repeat (NB-LRR) class. The C-terminal LRR region is thought to provide recognition specificity, while the N-terminal NB containing region activates downstream signalling leading to a defense response. Previous results from our lab demonstrated that, in the R gene (Rx), the LRR region can be artificially evolved to recognise viruses undetected by the wild type Rx protein. However, some of these broad recognition versions suffer from a reduced activation response, with deleterious consequences on plant fitness. During my doctoral research, I performed random mutagenesis on the N-terminal activation domains of a broad recognition version of Rx, and screened approximately 1500 clones for increased activation characteristics. I isolated four Rx mutants that show increased defense response without constitutively activating the protein, while retaining the broad recognition phenotype. Through homology modelling, we also revealed that these mutations concentrate around the ATP /ADP binding site, which is conserved across all known NB-LRRs proteins. This strategy of targeted evolution, where recognition and activation characteristics are sequentially modified, could potentially be employed to improve disease resistance in crops.

This talk is part of the Plant Sciences Research Seminars series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity