Developing stronger soybeans
By Julienne Isaacs
Cultivated soybean (Glycine max) variety (left) and recombinant inbred line of soybean (right) derived from an interspecific cross with soybean’s wild progenitor, Glycine soja. Both lines are part of the genomic panel illustrating differences in leaf shape, size and plant architecture. Photo by Robert Bruce.
Since Istvan Rajcan began working in soybean breeding in 1998, his team has developed 54 commercial soybean varieties.
The University of Guelph scientist is heading up a major research effort pinpointing genetic markers to develop high-yielding, high-quality soybean varieties. Rajcan, along with research partners Chris Grainger, Francois Belzile (Laval University), Milad Eskandari (Guelph – Ridgetown) and Robert Bruce (PhD candidate, Guelph), is studying a diverse panel of ancestral soybean lines, looking for traits that will improve varieties developed for Ontario, Quebec and southern Manitoba soybean producers.
The program has two main research focal points, one of which analyzes yield and soybean seed quality traits for potential niche market applications; the other looks at the genetics of disease resistance.
Rajcan received a Natural Sciences and Engineering Research Council Collaborative Research and Development Grant in 2013, matched with funding from industry partners Grain Farmers of Ontario (GFO), SeCan and Huron Commodities Inc. The four-year grant, which expires in 2017, follows on the heels of a previous study funded by GFO and the Growing Forward 1 Science Cluster.
“I’m grateful for the funding from the industry and federal government and I’m excited about the results we’re generating, which will help to make faster progress in soybean breeding,” Rajcan says.
The project relies on the investigation of plant history – namely, the ancestries of successful soybean lines.
Rajcan’s previous project looked at the dynamics of allelic variation in the “descendants” of a highly successful, high-yielding variety from the program: OAC Bayfield, which won the University of Guelph and SeCan’s Seed of the Year Award in 2013. “We looked at the parents, grandparents and great-grandparents of this variety to see which qualities had been passed on to make OAC Bayfield so successful, and we also looked at the progeny of OAC Bayfield to understand why it has been such a good parent for new varieties, also,” Rajcan says.
For the current project, the team has expanded the project beyond Bayfield, collecting a panel of close to 300 different soybean lines and varieties, including ancestral lines – a diverse panel of varieties dating back to the 1920s and 1930s, when commercial soybean breeding began in North America.
“We have the capacity, with our technology, to look at the alleles inherited from those ancestral lines that remain, and to look at alleles that have been lost over the generations of breeding,” Rajcan explains. “With that information, we can look at the chromosomes of soybeans and see which segments of the chromosomes have been conserved in successful varieties versus not-so-successful ones.”
This data tells the researchers which regions of the chromosomes are adapted for doing well in specific growing regions in Canada, and provides information about seed composition, such as isoflavones and fatty acids, and plant qualities, such as yield, maturity, and photosynthetic capacity.
So far, Rajcan’s team has genotyped the panels, or analyzed them using molecular markers. “Now, we’re collecting phenotypic information,” Rajcan says. “Robert Bruce, my PhD student, has started harvesting some material already, and there will be one more year (next year) of collecting phenotypic information. The next step is associating those phenotypes or traits with genetic information on the lines from the panel, using various genetic and bioinformatics software packages.”
The project’s final results will be collected by 2017, but since the beginning, Rajcan’s team has put their knowledge to good use, implementing it on the go in new breeding populations. “In my program every year we work with 120 populations from as many crosses, and they’re at all stages depending on when we made the cross, from F1 to F8, the highly homozygous true-breeding population,” he says.
Genetic material is delivered to industry partners SeCan and Huron, which commercialize the varieties year-to-year.
Rajcan’s program is aimed first at achieving higher seed yield in soybean varieties.
“For every soybean breeder that’s the main focus, and yield itself is a very complex trait conditioned by a large number of genes,” he says. “It’s not easy to breed for yield but we all do it. Yield is the result of everything that happens to the plant – that brings into the picture the plant’s ability to resist abiotic stresses like drought, waterlogging, heat or frost-tolerance; or biotic stresses like pests and diseases.”
But beyond breeding for soybean yield and food quality, Rajcan’s lab has smaller projects developing varieties with traits suitable for non-food industries, such as the paint and auto-parts industries. “We’ve developed a variety with very high linoleic acid (18:2), which is very important for paints and polyurethane for interior parts of various vehicles,” he says.
“Various industries that manufacture paints, varnishes, lubricants and auto-parts are currently using crude oil as the feed stock in processing, and they could use a renewable source such as soybean oil for the same purpose.”
Through Soy 20/20, a not-for-profit organization that connects government, academic and industry representatives for the development of Canada’s soybean industry, Rajcan’s team has been linked directly with a variety of end-users. “Soy 20/20 makes these connections and arranges meetings with reps from, for example, the paint industry. They find out from them what they need, and then we can answer whether we can do this, and how long it will take.”
The project is truly collaborative – Rajcan’s team also meets annually with GFO representatives to report on the study’s findings, who, in turn, communicate that information to their membership. “The information we generate is ultimately for the soybean breeders, and they see that as valuable. The practical value for the farmer comes from developing better and more productive new varieties using technologies that we develop,” he says.
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