BioOS: A Gene-Driven Digital Twin Runtime for Emergent Plant Development

Abstract

Predicting plant phenotypes from genomic data requires models that bridge molecular regulation and organ-scale morphogenesis. We introduce BioOS, a computational runtime in which plant behavior - cell division, differentiation, and elongation - emerges from the execution of a gene regulatory network rather than from hardcoded rules. The system is built on the Formal Cell abstraction: a minimal signal-processing unit analogous to the McCulloch-Pitts formal neuron, whose transfer function is gene expression. Each Formal Cell evaluates promoters, transcribes mRNA, translates proteins, and derives its entire behavioral repertoire from the resulting protein concentrations - without a single hardcoded rule in the simulator code. A multi-scale architecture with level-of-detail switching enables real-time simulation of Arabidopsis thaliana primary root development. On the current official five-case primary-root auxin benchmark, BioOS achieves 75.4% mean score, 5/5 qualitative matches, 5/5 cases passing all current gates, and Spearman severity correlation ρ = 0.70. The current root-auxin runtime is driven by a curated 35-gene registry with explicit promoter logic, kinetic parameters, and epigenetic state; for readability, this manuscript details a core 18-gene subnetwork that carries the main auxin benchmark logic. We describe the architecture, the gene expression runtime, the epigenetic memory model, the completed transition to post-hoc (non-causal) zone classification, and candidate benchmark extensions for persistent plasmodesmata and intracellular auxin compartmentalization within a broader six-suite, 63-case benchmark framework. Beyond the root-auxin slice, the current codebase also closes the official flowering (5/5), photosynthesis (7/7), and cytokinin (5/5) gates, while root-patterning remains a passing candidate panel.

Plant phenotyping relevance

植物の発生表現型を遺伝子制御モデルから予測する計算ランタイムの開発と、根の発生ベンチマークによる評価が中心であり、単なる生物学的測定ではない。

Code and data availability

The supplied blocks describe the BioOS simulation runtime, gene registry, and benchmark results, but contain no data or code availability statement, no public repository, no deposited phenotype datasets, images, or author analysis code with a public URL. The only URL present is the preprint DOI itself, which is the un-

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