A new gene optimization from Evogene is being incorporated into its multi-year collaboration with Monsanto. This Evogene news release says the addition of these new capabilities, designed to optimize desired trait efficacy and potentially accelerate product development, is part of a long identification and validation program by Evogene that has put more than 1,000 genes into Monsanto’s product development pipeline. This collaboration focuses on transgenic approaches for improved yield and enhanced stress tolerance in corn, soybean, cotton and canola.

Tom Adams, Global Biotechnology Lead at Monsanto stated: “We continue to be very pleased with our long-term collaboration with Evogene, as we look to bring to market new products that help farmers increase their productivity. As a valuable complement to Evogene’s proven gene discovery capabilities, we have recently also been very impressed with Evogene’s comprehensive gene optimization platform, which has the potential to accelerate our product development efforts. This has led us to devote a substantial portion of our remaining joint efforts under our current collaboration to applying these innovative technologies.”

Ofer Haviv, Evogene President and CEO stated: “Our collaboration with Monsanto is a substantial and important component of our company’s trait research and discovery activities. During the past six years, both teams have built a very strong and integrated relationship through the consistent sharing of knowhow and learnings, and the relationship continues to grow and evolve as we work together to bring yield and stress products to market. A key and increasing focus of our current efforts is to utilize more recently developed Evogene tools and systems in a comprehensive program for gene optimization, particularly with respect to gene combinations and trait stability. We are confident that our competitive advantages in these areas will have a significant impact on the probability of success for achieving novel end- products with substantial value to farmers.”

This gene optimization platform allows for advanced computational tools for defining the optimal expression pattern for a candidate gene, for assessing the ability of the gene to perform consistently across different varieties of the target crop, and for identifying novel gene combinations that improve crop performance.