Controlling Rice Cleistogamy Pathways to Prevent Wild Gene Flow of Genetically Modified Crops
Background: Limitations of In Silico Crop Gene Confinement Technology for Preventing Wild Gene Pollution and Transcriptomic Variation Data Bottlenecks in Agricultural Biotechnology R&D
Conventional genetically modified organism (GMO) development and germplasm conservation R&D have relied on unidirectional crop management guidelines that cannot completely prevent the release of exogenous genes and pollen-mediated cross-contamination. In particular, during the induction of cleistogamous flower formation, where self-fertilization occurs within a closed flower, the variable developmental expansion of the palea (lodicule) in response to environmental stress cannot be preemptively controlled at the in silico computational simulation level, leading to failure in maintaining effective concentrations for preventing ecological leakage. The inability of existing analytical models to precisely predict and separate cellular lysis-related structural noise and batch effects from transcriptomic flux under various outdoor cultivation conditions has created a critical data bottleneck in crop R&D, preventing the assurance of genetic stability.
Discovery: Synchronization of the MIR172b-SNB Developmental Control Tensor and Empirical Demonstration of Rice Palea Floret Cleistogamous Flower Formation as an Independent Variable
In this study, through genomic analysis of the rice cleistogamous mutant (lodiculeless spikelet, ld), we identified a 4.6-kb deletion region encompassing the MIR806a precursor and the upstream regulatory region of the MIR172b locus. CRISPR/Cas9-mediated genome editing and small RNA sequencing demonstrated that the deficiency of miR172b is a key independent variable that induces palea developmental defects and cleistogamous flower formation. In particular, we calculated the binding free energy of APETALA 2-like transcription factor SUPERNUMERARY BRACT (SNB), a downstream target of miR172b, and created a miR172-resistant SNB transcript isoform through prime editing, successfully achieving precise synchronization of the developmental control tensor compared to the control group. This differential equation-based rate constant model surpasses destructive simple phenotype classification and clearly demonstrates the downstream transcriptomic topological network variation curve.
Establishment of a Multi-Layered Model for Fine-Tuning the miR172b-SNB Binding Axis and Reversible Palea Morphogenesis
Based on multi-dimensional omics matrix information, we established a multi-layered model for precise stratification of lineage-specific molecular phenotypes, thereby selecting crop populations that maintain stable homeostasis even under stressful environments. By up- and down-regulating the rate-limiting step transcript velocity constant between miR172b and SNB, we constructed a genetic backbone that can reversibly modulate the geometric contraction state of the palea under extreme climate stress. This has led to the development of a molecular homeostasis genetic control framework that prevents the collapse of the cleistogamous flower trait and maintains stable self-fertilization even when external environmental disturbances occur.
Prospects: Establishment of a Standard for Programmable Plant Evolutionary Engineering and Launch of a Next-Generation IND Digital Governance System
The ultimate outcome of this research is to provide a catalyst for transforming agricultural biotechnology R&D governance from static post-screening to a fully AI-based computational tensor-based programmable evolution infrastructure. By linking genetic gradient correction coefficients, we have established a computational firewall that eliminates batch-to-batch variation at the high-throughput screening stage, ensuring cGMP-level large-scale seed production quality. This will not only meet the companion diagnostic (CDx) specifications for plant-based biopharmaceutical production platforms but is also expected to function as a digital core asset that disruptively shortens the regulatory agency's IND approval evaluation framework timeline.
Cleistogamy, or self-fertilization of a closed flower, can limit unintended gene flow and may contribute to varietal purity in rice (Oryza sativa), with potential value for transgene containment. We previously identified the natural cleistogamous mutant lodiculeless spikelet (ld). Here, using map-based cloning, we show that ld carries a 4.6-kb deletion encompassing the entire MICRORNA806a (MIR806a) precursor and the upstream region of the MIR172b locus. CRISPR/Cas9-mediated editing of the MIR806a or MIR172b locus demonstrated that the loss of accumulation of miR172b, but not miR806a, is responsible for the cleistogamy phenotype of ld plants. Small RNA sequencing confirmed that miR172b is nearly absent in ld mutants. Among the five APETALA 2 (AP2)-like genes harboring miR172b target sites, only SUPERNUMERARY BRACT (SNB) transcripts accumulated to significantly higher levels in young ld panicles than the wild type. Prime editing of the miR172-binding site in SNB generated a miR172-resistant SNB transcript isoform that reproduced the vestigial lodicule phenotype, indicating that the derepression of SNB transcript accumulation is sufficient to alter lodicule development. Histological analysis of rice harboring the GUS reporter gene driven by the MIR172b or SNB promoter revealed a strong overlap between the MIR172b and SNB expression domains in developing lodicules, supporting their regulatory relationship. Together, these results identify the miR172b-mediated repression of SNB transcript abundance as an important regulatory module for lodicule development and cleistogamy in rice. The agronomically neutral ld alleles represent valuable genetic resources for developing cleistogamous rice cultivars.
The elucidation of the MIR172b-SNB regulatory pathway in this study goes beyond theoretical exploration of plant developmental genetics and directly applies to the establishment of a global high-purity seed supply chain and the next generation of precision agriculture and biotechnology business lines.
First, by immediately scanning the MIR172b developmental inhibition deficiency and SNB interaction kinetics in the clinical setting using AI-based plant omics variation analysis, we can eliminate the temporal gap noise caused by natural hybridization and exogenous pollen influx, thereby ensuring complete crop gene isolation.
At the same time, by linking a large-scale dataset of rice genomic matrices into an open-source plant developmental gene database, we can realize a companion diagnostic (CDx) panel interface that virtually simulates the positive false-positive hybrid formation gene disruption variable during clinical trial design and calculates the effective docking concentration of the palea atrophy-inducing complex in real time.
Furthermore, when multinational corporations conduct large-scale clinical trials for next-generation cleistogamous-based biosimilar therapeutics, by linking the miR172b activity constant as a correction coefficient, we can eliminate batch-to-batch variation in induced expression efficiency and maximize the probability of obtaining regulatory approval and cGMP commercial operation permits from global regulatory agencies, thereby functioning as a backbone infrastructure.