Abstract

Developmental processes in angiosperms are often studied using model species, such as Arabidopsis thaliana. However, non-model plants exhibit distinct processes, such as the flower-to-fruit transition (FFT), which, in species like Vanilla planifolia, involves post-pollination syndrome (PPS). Unlike model species, where ovules are fertilized shortly after pollination, Vanilla ovules develop over a span of 25 days post-pollination (DPP). Consequently, these plants are sensitive to environmental fluctuations, leading to ovary drop and reduced fruit set if pollination is incomplete.

Due to limited genomic data and the unique nature of PPS in Vanilla, identifying the genetic networks and hub genes involved in this process remains challenging. This study proposes employing molecular phenology and co-expression network analysis to identify transcriptional regulation cores associated with the FFT in Vanilla planifolia. The proposed workflow consists of four phases: (1) a review of the literature and a theoretical model of genes involved in FFT, (2) molecular phenology analysis of gene expression and anatomical changes, (3) data mining and genetic orthology to identify ancestral genes, and (4) transcriptional regulatory core identification through co-expression network analysis.

This approach will generate bioinformatic tools applicable not only to Vanilla but also to other non-model species. By identifying conserved transcriptional regulation cores and candidate genes for functional validation, this study offers novel insights into the molecular mechanisms underlying FFT in orchids, with broader implications for research on non-model plants.