Soybean-PIPE): A Computational Approach in Soybean Functional Genomics


Bahram Samanfar, Elroy Cober, Stephen Molnar, Brad Barnes, James Green, Frank Dehne, Ashkan Golshani: (Soybean-Human PIPE): A Computational Approach in Soybean-Human Functional Genomics. Plant Biology, 2018, Montreal, Canada.


Soybean is one of the major Canadian grain crops and its production is expanding in Canada with the majority of the increase in short season areas (Western Canada and northern regions). The list of novel factors affecting these pathways in soybean, and in model plants like Arabidopsis, continues to grow suggesting the presence of other novel players which are yet to be discovered.
The soybean Protein-protein Interaction Prediction Engine (Soybean-PIPE) is a computational tool used to predict protein-protein interactions (PPI) in soybean. Theoretically, if a gene interacts with groups of genes involved in one specific pathway, that gene might also be involved in that specific pathway (“guilt by association”). Our knowledge of global PPI networks in complex organisms such as human and plants is restricted by technical limitations of current methods.
Briefly, PIPE searches for re-occurring short polypeptide sequences between known interacting protein pairs and novel proteins and predicts interactions based on protein sequence information and a database of known interacting protein pairs. PIPE has been used to produce proteome-wide, all-to-all predicted interactomes in a variety of organisms including yeast human, Arabidopsis and others. It has also been shown that PIPE has the ability to produce cross-species predictions, Soybean-SCN and Soybean-Human.
Currently we are using PIPE towards predicting the first comprehensive protein-protein interaction network for soybean ever generated. In an independent study (Samanfar et al., 2017), we have used three different approaches; bioinformatics (Soybean-PIPE), classical plant breeding, and molecular biology (analysis of SSR and SNP haplotypes) to identify a novel gene involved in time of flowering and maturity in soybean.
Identification of molecular markers tagging the PIPE-identified genes controlling flowering and maturity in soybean will allow soybean breeders to efficiently develop varieties using molecular marker assisted breeding.

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