Background: Limitations in Responding to Climate Change-Induced Environmental Stress and Bottlenecks in Micronutrient Biosynthesis Gene Data for Crop R&D

• Amidst the recent revisions to the U.S. USDA SECURE rule and the trend of easing regulations on gene-edited crops led by global agricultural biotechnology companies such as Corteva Agriscience and Syngenta, the pace of crop improvement for addressing climate change and hidden hunger is accelerating at an unprecedented rate. However, existing linear and static genomic analysis standard guidelines have critical limitations in precisely simulating dynamic and complex stress response pathways in outdoor environments within an in silico computational environment. Specifically, they fail to control for issues such as cell lysis-induced structural degradation noise, the significant differences between laboratory and field conditions, and unwanted feedback inhibition fluxes in real-time, repeatedly failing to maintain effective seedling survival rates and pathogen prevention concentrations, thereby creating a serious bottleneck in R&D data. In the absence of integrated multi-dimensional genomic data, it has been fundamentally difficult to control the complex metabolic pathways of micronutrients linked to environmental stress, which has been a critical computational barrier hindering the expansion of the R&D pipeline.

Discovery: Implementation of a Multi-Target CRISPR-Cas Variant Algorithm and Empirical Demonstration of Single-Cell Resolution Tensor Synchronization of Independent Variables

• In this study, we successfully implemented a multi-target CRISPR-Cas variant modality that simultaneously targets multiple gene trajectories, and demonstrated the synchronization of genetic independent variables into multi-dimensional tensors at the single-cell level. We precisely tuned the intermolecular binding free energy involved in DNA double helix binding in silico, and proactively calculated enzyme reaction rate constants based on differential equations to completely eliminate off-target and batch effects of gene scissors computationally. This significantly surpasses the predictive power of existing simple gene knockout models. By tracking and elucidating the topological variations of downstream transcriptome networks expressed under environmental stress conditions in real-time, we successfully verified the molecular biological precision and stable expression integrity of artificial genome engineering.

Establishment of a Model for Coordinating Complex Stress Response Pathways and Layered, Reversible Homeostasis

• Based on multi-dimensional omics matrix information, a precision stratification model was established to classify the genetic phenotypes and nutritional composition of climate-adaptive crops. The research team targeted the reactive oxygen scavenging pathway and the biosynthesis/transport system of essential micronutrients, iron and zinc, and precisely up-regulated or down-regulated each reaction pathway by regulating the rate-limiting step constants that determine genetic activity at the molecular level. This successfully established a genetic backbone architecture that enables crops to autonomously maintain reversible homeostasis even under environmental anomalies such as drought and high salinity, and precisely guides the plant's metabolic flux towards optimal accumulation pathways for alleviating nutrient deficiencies.

Prospects: Establishment of a Programmable Synthetic Biology Standard and Implementation of a Next-Generation IND Digital Governance System

• The establishment of this architecture marks a turning point in global bio-crop R&D governance, shifting from a static, post-hoc evaluation system to a fully reset, AI-based, multi-dimensional tensor-based programmable infrastructure. In the process of expanding global biotech pipelines, it automatically links the genetic gradient correction coefficient in the high-throughput screening stage and eliminates batch-to-batch expression variations, securing a strong technological computational moat. Ultimately, it will function as a backbone infrastructure that meets the companion diagnostic (CDx) standards in the digital healthcare field, links a bio-monitoring system, maximizes the probability of obtaining IND clinical trial submissions and cGMP commercial production licenses from global regulatory agencies, and drastically shortens the approval timeline.