PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes.
Li C, Zhang Q, Chen H, Lin K, Luo C
Synthetic Biology
Disease resistance genes — the ones that determine whether your tomatoes survive late blight or your beans shrug off a virus — could soon be designed by AI rather than hunted across decades of wild plant surveys and breeding trials.
Scientists trained an AI on the DNA blueprints of 12 different plant species and taught it the grammar of how plant genes are written. The AI then invented completely new gene sequences that don't exist in nature. When researchers tested seven of these invented genes in tobacco plants, all seven actually turned on and produced RNA, and two went all the way to making stable proteins — proving for the first time that an AI can write plant genes that real plants can read and use.
Key Findings
PlantGFM was pre-trained on 10.84 billion nucleotides from 12 plant species and matched or exceeded specialized gene-prediction software after fine-tuning on 10 annotated plant genomes.
All 7 AI-designed gene candidates showed transcriptional activity (RNA production) when introduced into Nicotiana benthamiana plants.
2 of the 7 AI-invented genes achieved stable protein expression — the first demonstration of full DNA-to-RNA-to-protein activity from large-language-model-generated sequences in any plant.
chevron_right Technical Summary
Researchers built an AI called PlantGFM that learned from nearly 11 billion letters of plant DNA across 12 species, then used it to write brand-new plant genes from scratch — and those invented genes actually worked inside a living plant, producing proteins for the first time.
Abstract Preview
The artificial intelligence (AI)-driven generation of genetic sequences holds transformative potential for addressing global challenges in agriculture, medicine, and bioenergy. Traditional approach...
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