Circadian Transcriptomic Dynamics Identify Transferable Retina-Choroid Expression Patterns in Myopia Development via Multistage Machine Learning.

Circadian regulation has emerged as an important modulator of ocular growth; however, its role in organizing retina-choroid transcriptomic responses during myopia development remains incompletely understood. In this study, we reanalyzed publicly available retinal and choroidal RNA-seq datasets from chick models of form-deprivation myopia using a multistage machine learning framework. A biologically motivated ZT8/12 circadian window was defined from prior published time-of-day transcriptomic evidence and evaluated using feature selection, cross-tissue and cross-stage validation, and external validation in an independent retinal dataset. Machine learning models classified the ZT8/12 window with high performance across onset and progression datasets, and control analyses indicated that this signal reflects a broad transcriptome-wide temporal state rather than a pattern unique to the 53-gene signature. The final gene signature is therefore interpreted as a stable representative subset of the ZT8/12-associated expression state. Cross-species functional enrichment and ortholog mapping suggested hypothesis-generating functional relationships between chicken genes and human orthologs. Overall, this work provides a computational framework for evaluating time-associated expression patterns in myopia and highlights circadian timing as a candidate component of retina-choroid biology requiring further functional validation.