Principal Investigator: Bahram Samanfar
Research Institution: Agriculture and Agri-Food Canada (AAFC)
Timeline: April 2019 – March 2022
- To investigate host-pathogen interaction between soybean and SCN by running PIPE (software) to obtain a list of soybean-SCN interacting protein pairs using a computational approach which investigates all soybean proteins against all SCN proteins.
- To validate predicted protein interactions using molecular biology related approaches.
- To investigate sequence databases (SNP, re-sequencing) for nucleotide variations (allelic variations) for the candidate genes predicted by PIPE in soybean. Variations at these target genes might have effects on the protein interactome (to be re-investigated by PIPE) and may identify new SCN resistance genes.
- To perform greenhouse SCN screening of candidate soybean lines having genetic variations at the target genes identified by PIPE.
- To develop allele-specific markers for the candidate genes as potential sources of resistance to SCN which will allow for marker assisted selection in breeding programs.
- There is a gap of knowledge in understanding the interaction between soybean and SCN. This computational approach will shed light into this complicated pathway and will identify new interactions between soybean and SCN.
- For any identified gene in soybean interacting with SCN, we will investigate the variation for that specific gene and use it as a potential new resistance source which could have application in Ontario adapted SCN-resistant line development.
- For a given gene in soybean which interacts with virulence genes from SCN, another option could be the application of gene knock-out (i.e., CRISPR) or knock-down (i.e., RNAi) to generate a new SCN resistance source.
- Results from this proposal will be used by soybean breeders for marker assisted selection to generate Ontario-adapted SCN-resistant lines which will allow Ontario farmers to perform farming activities more economically.
Soybean cyst nematode, SCN (Heterodera glycines), was first found in Ontario in 1988 (southwestern regions) and continues to spread to shorter season areas. The problem is once SCN is present in a field, eradication is impossible. Management options are resistant lines, crop rotation and field management. Yield loss could vary between 5-80%. There are limited sources of resistant genes used in soybean and in some areas with long exposure to SCN we have started to see resistance breakdown.
In order to identify more SCN resistance genes, we propose to develop and use a bioinformatics tool to investigate host-pathogen interactions between soybean and SCN using a protein-protein interaction approach. The Protein-protein Interaction Prediction Engine (PIPE) is a computational tool developed by our collaborators at Carleton University and is used to predict protein-protein interactions (PPI). PIPE has been used to produce proteome-wide, all-to-all predicted interactomes in a variety of organisms including yeast, human, soybean, Arabidopsis and others. In this way, the investigation of global PPI of SCN will give us a better understanding regarding functional biology of this nematode; and more importantly, we will have the opportunity to investigate host-pathogen interactions between soybean and SCN in a comprehensive manner. This will lead us to the identification of novel target genes either in soybean or SCN which will provide a better understanding of the virulence process of SCN and will provide novel candidates for new SCN resistance genes.
External Funding Partners:
This project is funded in part by the Canadian Agricultural Partnership, a five-year, $3 billion investment by federal-provincial and territorial governments.