‘Ultimate’ chickpea model developed

University of Queensland – A broad international research effort has led to development of a genetic model for the ‘ultimate’ chickpea, with the potential to lift crop yields by up to 12 per cent, according to a new study published in the journal Nature.

The research consortium genetically mapped thousands of chickpea varieties, and a team at the University of Queensland team used this information to identify the most valuable gene combinations using artificial intelligence (AI).

Professor Ben Hayes led the Queensland component of the project to develop a ‘haplotype’ genomic prediction crop breeding strategy for enhanced performance for seed weight.

“Most crop species only have a few varieties sequenced, so it was a massive undertaking by the international team to analyze more than 3000 cultivated and wild varieties,” Hayes said in a news release.

Canadian researchers at the University of Saskatchewan were also involved with the study, sequencing the genetics of 200 Canadian chickpea plants.

“Chickpeas are one of the main protein sources for hundreds of millions of people — especially in South Asia, Africa and other parts of the world,” said Bunyamin Tar’an of the University of Saskatchewan in a separate news release. “The research provides an avenue to support global efforts to develop chickpeas with even better nutritional value as well as more climate-resilient varieties.”

The landmark international study was led by Rajeev Varshney from the International Crops Research Institute for the Semi-Arid Tropics in Hyderabad, India. The study confirmed chickpea’s origin in the Fertile Crescent and provides a complete picture of genetic variation within chickpea.

“We identified 1,582 novel genes and established the pan-genome of chickpea, which will serve as a foundation for breeding superior chickpea varieties with enhanced yield, higher resistance to drought, heat and diseases,” Varshney said.

Hayes said the Queensland team used the data to model a chickpea with perfect genetics for seed weight, a trait linked to yield.

“This additional data led to the increase in yield predicted by our model, which is still being fine-tuned,” he said.

“We are using our AI ‘FastStack’ technology platform to design a chickpea with the ultimate genetics for maximum seed weight, and we think this will ultimately be a valuable tool for chickpea breeders.”

FastStack combines AI with genomic prediction technology to identify the combinations of genes most likely to improve crop performance.