Abstract Detail

Genomics / Proteomics

Samanfar, Bahram [1], Cober, Elroy [2], Charette, Martin [1], Schoenrock, Andrew [3], Dehne, Frank [4], Golshani, Ashkan [5], Molnar, Steve [1].

A functional genomics approach (PIPE, Protein-protein Interaction Prediction Engine) to identify new early maturity alleles in soybean for Western Canada.

Soybean is one of the major Canadian grain crops; the Canadian soybean seeded area was ~5.4 million acres in 2015. Soybean production is expanding in Canada with the majority of the increase in short season areas (Western Canada and northern regions). The development of short season (early flowering and maturity) soybeans for Western Canadian and northern regions requires effective use of early maturity genes. Eleven maturity loci have been reported in soybean; however for almost half of those loci the molecular basis is not yet clear. 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. Protein-Protein Interactions (PPIs) are essential molecular interactions that define the biology of a cell, its development and responses to various stimuli. Theoretically (“guilt by association”), if a gene interacts with groups of genes involved in one specific pathway, that gene might also be involved in that specific pathway. Our knowledge of global PPI networks in complex organisms such as human and plants is restricted by the technical limitations of current methods. The Protein-protein Interaction Prediction Engine (PIPE) is a computational tool 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 (Saccharomyces cerevisiae), human (Homo sapiens), Arabidopsis and others. Currently we are using PIPE towards predicting the first comprehensive protein-protein interaction network for soybean. To test whether PIPE has the ability to predict PPI in soybean and then to predict novel genes involved in flowering and maturity, we have used three complementary approaches; classical plant breeding, molecular biology (analysis of SSR and SNP haplotypes), and PIPE predicted PPI. This strategy successfully identified a new maturity locus tentatively called “E₁₀” and the underlying candidate gene. More importantly, further comprehensive investigation of the soybean genome will lead to Identification of molecular markers tagging the genes controlling flowering and maturity in soybean, which will allow soybean breeders to efficiently develop varieties using molecular marker assisted breeding. Allele specific markers will allow stacking of early maturity alleles to develop even earlier maturing cultivars. This bioinformatics approach to PPI will also help to bridge the knowledge gap regarding the flowering and maturity pathway in soybean.

1 - Agriculture and Agrifood Canada, AAFC, Ottawa Research and Development Centre (ORDC), 960 Carling Avenue, Neatby Building (#20), Ottawa, ON, K1A 0C6, Canada
2 - Agriculture and Agri-Food Canada , Ottawa Research and Development Centre (ORDC), 960 Carling Avenue, Ottawa, ON, K1A 0C6, Canada
3 - Carleton University, School of Computer Science, 1125 Colonel By Dr, Ottawa, ON, K1S 5B6, Canada
4 - Carleton University, School of Computer Science, 1125 Colonel By Dr, Ottawa, ON, K1S 5B6, Canada
5 - Carleton University, Biology, 1125 Colonel By Dr, Ottawa, ON, K1S 5B6, Canada

Keywords:
Soybean
Early maturity
Flowering pathway
E₁₀
SSR
SNP
Bioinformatics
PPI
PIPE
Functional genomics.

Presentation Type: Oral Paper
Session: 27, Genomics & Proteomics II
Location: 105/Savannah International Trade and Convention Center
Date: Tuesday, August 2nd, 2016
Time: 2:15 PM
Number: 27004
Abstract ID:42
Candidate for Awards:Margaret Menzel Award