A new artificial intelligence model has been developed to understand the genetic “language” of plants, a breakthrough that could reshape plant science and agriculture.
The model, named Plant RNA-FM, is believed to be the first of its kind. It was trained on data from plant ribonucleic acid (RNA), a key molecule that plays a crucial role in cellular communication and growth within plants.
RNA, which is similar to DNA, helps plant cells coordinate their growth and development by transmitting information between them. The AI model was trained using a dataset of 54 billion RNA sequences from 1,124 plant species worldwide. Researchers say it has learned to recognize the underlying patterns and logic of RNA, much like how OpenAI’s ChatGPT understands and responds to human language.
“Although RNA sequences may seem random at first glance, our AI model has learned to identify hidden patterns within them,” said Dr. Haopeng Yu, a postdoctoral researcher at the John Innes Centre in England.
The research, published in Nature Machine Intelligence on Monday, was led by scientists at the John Innes Centre and the University of Exeter, with contributions from the Northeast Normal University and the Chinese Academy of Sciences.
Understanding RNA’s Role in Plants
Using the model, researchers have been able to predict how RNA functions and identify key RNA structures that influence important plant processes like stress response and growth. These RNA structures act as a “language” that helps control the translation of genetic information into proteins—a vital process for almost every cellular function, including chemical reactions.
The team validated the model’s predictions through experiments, confirming that RNA structures identified by the AI impact protein translation efficiency.
Potential for Agricultural Innovation
The breakthrough is expected to have far-reaching implications for plant science. The researchers hope the AI model will help unlock new methods for improving crops and advancing gene design. Professor Yiliang Ding, who leads the John Innes Centre’s group, said this innovation could be pivotal in developing crops that are more resilient to climate change and more efficient in feeding a growing global population.
“AI is playing an increasingly important role in helping plant scientists address challenges, from improving crop yields to creating plants that can adapt to new environmental conditions,” Ding said.
The team also believes their work could extend beyond plants, with potential applications in research involving invertebrates and bacteria.
In summary, this new AI-powered model opens up exciting new possibilities for understanding the genetic codes of plants, with the potential to revolutionize agriculture and environmental science.
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