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Improving Crop Resilience with AI and DNA Synthesis

High-fidelity oligo synthesis was key for experimentally confirming AI-predicted DNA sequences linked to favorable gene expression changes controlling desired crop traits.

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Feeding a growing global population requires faster and smarter approaches to crop development. Researchers at Phytoform Labs, a crop trait development company, combine AI-driven DNA design with CRISPR techniques to engineer more resilient plants. However, experimentally validating their variants on a large scale can be challenging.

Recently, Phytoform scientists overcame this bottleneck while searching for promoter variants linked to drought resistance in tomatoes. By employing Twist Bioscience’s high-fidelity oligo pools, the researchers accurately tested 2,000 promoter variants to identify ones that drove increased gene expression.

Download this case study to learn how researchers at Phytoform Labs used AI predictions and precision DNA synthesis to accelerate trait engineering in plants.

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