It might come as a surprise, but many of the plants in a typical salad actually have more genes than you do. That doesn’t make them more complex than humans, but it does show that they are built for adaptability.

Plants can’t move when conditions change. Instead, they rely on their genetic diversity to adapt to shifts such as climate change, pest outbreaks, soil variation, and changing farming practices. But with these factors constantly in flux, plant breeders face an almost impossible task: improving crops for current conditions without limiting their ability to adapt to unpredictable conditions in the future. As breeders work to improve how plants perform, their target is constantly moving.

Part of the challenge lies in the biology itself. Plants have evolved a wide range of genetic traits to survive in different environments. While these traits can be beneficial under certain conditions, they don’t act in isolation. Instead, they interact in complex ways with each other and with the environment. This is known as gene–environment interaction, where factors like weather, soil conditions, and pests influence how genes are expressed. Together, these interactions shape a plant’s traits, making it difficult to pinpoint which genes are actually driving success in any given environment.

A new follow-up study from researchers at Corteva Agriscience explores this challenge, showing that the way we organize breeding programs can shape not just how quickly crops improve, but how well they keep up with a changing world.

This study builds on earlier work by the same research team, which explored why traditional breeding programs that have often been decentralized and reliant on a small number of elite plant lines have been so successful. That work showed that narrowing the range of genetic possibilities can actually help breeders make progress when dealing with complex genetics. The new study takes this idea a step further, asking what happens when those strategies are applied in a constantly changing environment.

To explore this question, the researchers turned to computer simulations. Rather than testing breeding strategies in real crops (which can take years or even decades), they created virtual breeding programs that allowed them to model how breeding populations evolve over time under different conditions. These simulations captured the complexity of plant genetics and the reality of changing environments. The researchers then compared different ways of organizing breeding programs to see how each approach affected both short-term progress and long-term adaptability. They focused on three main approaches: centralized programs, where all breeding happens within a single large population; isolated programs, where smaller groups work independently; and distributed programs, where multiple groups operate separately but share genetic material over time. The results revealed a clear tension: the strategies that improve crops quickly in the short term can also limit their ability to adapt to future changes.

Isolated breeding programs were able to make faster progress early on. By narrowing their focus, they could more quickly identify and build on successful genetic combinations. But over time, these programs lost genetic diversity, limiting their ability to adapt as conditions changed.

At the other extreme, centralized programs maintained higher levels of genetic diversity, giving them more flexibility to respond to new challenges. But this broader approach often slowed progress in the short term.

The most effective strategy struck a balance between these two extremes. In distributed breeding programs, multiple groups worked independently while continuing to share genetic material. This structure allowed breeders to make steady improvements while preserving enough diversity to adapt to future conditions.

Together, these findings highlight a central challenge not just in plant breeding, but in genetics and evolution more broadly. Success in the present does not always prepare organisms for the future. In a world where environmental conditions are increasingly unpredictable, strategies that balance speed with flexibility may be key to sustaining both agricultural productivity and long-term resilience.

References

  • Technow F, Podlich D, Cooper M. Back to the future 2: the implications of germplasm structure on the balance between short- and long-term genetic gain in a changing target population of environments. G3: Genes|Genomes|Genetics. April 2026. 16(4). https://doi.org/10.1093/g3journal/jkag044

  • Technow F, Podlich D, Cooper M. Back to the future: implications of genetic complexity for the structure of hybrid breeding programs. G3: Genes|Genomes|Genetics. July 2021. 11(7). https://doi.org/10.1093/g3journal/jkab153 

Jenny Montooth is a science communicator and co-founder of The Science Underground. Jenny is passionate about using creative and innovative strategies to make complex topics engaging and accessible to wider audiences. You can follow Jenny on LinkedIn.

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