The global consortium was led by Dr. Isobel Parkin (PhD), research scientist from Agriculture and Agri-Food Canada (AAFC) and affiliate researcher at GIFS, Dr. Andrew Sharpe (PhD), director of genomics and bioinformatics from GIFS, and NRGene, a leading genomic artificial intelligence (AI) company based in Israel.
“Completing the sequencing of all the genomes and delivering the comparative pan-genome analysis has revealed the scope of genetic diversity that exists within the crop,” said Sharpe. “It truly is the final satisfying step of this rewarding initiative”.
The consortium included key players in the canola industry, among them Bayer, Corteva, Nutrien and NuSeed. Each member contributed their own canola lines and received the full pan-genome comparison results.
Canola is a major oil seed crop considered to be a high-quality vegetable oil and commonly used in food production and various industrial applications, including biofuel. It is farmed on approximately 35 million acres globally and with 85 million tons produced in 2019, according to the Food and Agriculture Organization. The results of the consortium’s research has immense economic value for Canada, which is one of the world’s leading producers and exporters of canola.
Extensive breeding of the crop across the world, is focused on developing higher yielding and more nutritional varieties that can naturally resist plant diseases. The use of DNA markers has already enhanced canola breeding over the past three decades. However, understanding its whole genome which is complex, diverse and unstable became a bottleneck in canola breeding.
Building a pan-genome database to unravel the broad genomic diversity in canola is key to expanding the crop’s productivity and will help increase its use for a range of applications - replacing lower quality vegetable oils and diesel fuels.
“The pan-genome is already revealing previously hidden novel structural variation that will prove invaluable in characterizing economically important traits of the crop,” said Parkin.
The international consortium generated a full genome sequence of 12 canola and rapeseed varieties that were assembled using NRGene’s DeNovoMAGIC™ software. Each genome was built from about one billion DNA chemical elements and differs on average from other genomes in 40 per cent of the DNA elements. These differences in the genetic content are responsible for the unique field performance of each variety.
To identify all of the unique DNA elements in each variety, NRGene performed an all-to-all comparison on the 12 chromosome-level genome sequences and built the pan-genome database.
“We are pleased that NRGene’s genomic AI tools were chosen by the leading canola research teams to build an accurate pan-genome,” said Dr. Gil Ronen, NRGene’s CEO. “With the great help of our consortium partners, we successfully created a valuable asset that will be used for the coming decades towards overcoming canola’s key breeding challenges.”
The canola pan-genome will be used by the consortium members, and following scientific publication, will be available to the entire canola breeding and research community to accelerate the genetic understanding of this important crop. Elite lines with key commercial traits will be developed rapidly and bring better quality products to market.