Multi-Omics Meta-Analysis of Transgene Integration Patterns and Long-Term Expression Stability in Plants

Transgene expression stability across generations represents a critical determinant of agricultural biotechnology success, yet the genomic and epigenomic factors governing integration site selection and long-term expression persistence remain poorly understood at a systematic level. This doctoral dissertation presents a comprehensive multi-omics meta-analysis synthesizing publicly available whole-genome sequencing, chromatin immunoprecipitation, and transcriptomic datasets to characterize transgene integration patterns and their relationship to expression stability in plants. A systematic data retrieval from Gene Expression Omnibus, NCBI Sequence Read Archive, GenBank, ChIP-Atlas, and Ensembl Plants yielded 1,046 records across six dataset categories, including 402 T-DNA flanking sequences from insertion collections and 50 transgenic expression studies comprising 1,927 samples across multiple plant species. Meta-analysis of expression stability revealed a pooled effect size of 0.530 (95% CI: 0.486-0.575), indicating moderate overall stability with substantial heterogeneity (I² = 50.8%). The most significant finding demonstrated a strong association between chromatin state and expression stability (χ² = 34.42, p < 0.0001), with transgenes in H3K4me3-enriched active chromatin exhibiting stable expression in 84.4% of cases compared to only 9.1% in Polycomb-repressed regions. Correlation analyses identified H3K4me3 as a positive predictor of stability (r = 0.594, p < 0.0001), while genic integration correlated negatively with stable expression (r = -0.524, p = 0.0001). Hierarchical clustering of multi-omics features identified five distinct integration site clusters with differential expression outcomes. These findings provide quantitative evidence for chromatin-mediated regulation of transgene expression and establish a predictive framework for identifying favorable integration loci, with significant implications for improving the efficiency and predictability of transgenic crop development.