PhenoGene: A New Tool for Plant Breeders

Published online: Mar 24, 2022 Articles, New Products
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Phenome Networks, in collaboration with KeyGene, introduces PhenoGene, a game-changing solution for plant breeders to optimize breeding strategies.

PhenoGene, based upon an algorithm developed by KeyGene, is now available as a novel module in the PhenomeOne software, as a decision support tool to optimize breeding strategies for any crop. The PhenoGene module enables breeders to design the ideal plant, the so-called ideotype, based on genetic trait information from multiple parents, and calculate the fastest and most efficient breeding schedule, to combine favorable traits from multiple parents into a single variety.

Plant breeders developing new varieties are faced with the challenge of developing the ideal genotype as fast as possible, especially when they need to combine favorable traits, as determined based on DNA markers (such as resistance genes, QTLs, etc.), from multiple sources into one novel variety. DNA markers linked to the traits that need to be combined are very helpful, but the best way to combine the traits into one variety or parental line is almost impossible to calculate. The PhenoGene algorithm provides the most efficient recipe for which crosses to perform, how many plants to use in each generation for each cross, and how many generations are required to achieve that requested genotype in the most efficient way mathematically possible.

Leaving Behind Trial and Error

During the past few decades, the data-based insight into the phenotype and the DNA of plants has exponentially increased. That may allow breeders to also include that knowledge in choosing the best approach to get to the ideal variety. This opens possibilities to make the process of choosing the best breeding approach into a data-based process, eliminating the trial and error in plant breeding.

Being a focal point in technology innovation for plant breeding, in fields like marker development and next-generation DNA sequencing, KeyGene was one of the first to understand the value of data-based optimization of breeding for ideal plants. KeyGene scientists, therefore, developed the so-called Crossing Scheme Optimizer. This algorithm considers marker distances and recombination probabilities when designing the optimal breeding approaches.

Supporting Plant Breeders

This optimizer is already being used by a number of partners of KeyGene. In discussions with Phenome Networks, KeyGene scientists recognized the value of converting this optimizer into a user-friendly tool integrated into the PhenomeOne software suite, in order to make it available for a large number of breeders across the globe.

Phenome Networks is the company behind the well-known PhenomeOne package that already supports thousands of breeders all over the world in data collection, data management, and breeding intelligence. The breeding optimizer is made available as a module called PhenoGene of the PhenomeOne package on a SaaS (Software as a Service) basis.

Best, Fastest and Lowest-Cost

Using the tool, breeders can develop and compare different breeding strategies to integrate beneficial traits from multiple parents. Moreover, the results of the algorithm show the total costs and time that it takes to develop a particular variety, which can be reviewed by breeders and matched to the actual resources and time to market.

“Our team is thrilled that PhenomeOne users now get access to KeyGene’s powerful Crossing Scheme Optimizer algorithm through our PhenoGene module, which will bring breeding for the ideal variety or parental line within reach for breeders in many crops and regions,” says Yaniv Semel, CEO of Phenome Networks.

“We are very happy that our decision support tool for breeders is now available to a large audienc, through this unique collaboration with Phenome Networks,” says Arjen van Tunen, CEO of KeyGene. “The implementation of the software in PhenomeOne makes it very easy to use and will allow breeders to build various scenarios in just minutes and evaluate them based on time, cost and complexity. We are sure this opportunity will contribute positively to the efficiency of the breeding process in many crops, in many organizations”