A Quantitative and Dynamic Model of the Arabidopsis Flowering Time Gene Regulatory Network

• DOI: 10.1371/journal.pone.0116973
• Publication Date: 2015-02-26T18:49:38Z
• Authors: Felipe Leal Valentim; Simon van Mourik; David Posé; Min C. Kim; Markus Schmid; Roeland C. H. J. ...; Marco Busscher; Gabino F. Sanchez...; Jaap Molenaar; Gerco C. Angenent; Richard G. H. Immink; Aalt D. J. van Dijk
• Keywords: Leafy; Gene regulatory network; Vernalization

Various environmental signals integrate into a network of floral regulatory genes leading to the final decision on when flower. Although wealth qualitative knowledge is available how flowering time regulate each other, only few studies incorporated this predictive models. Such models are invaluable as they enable investigate various types inputs combined give quantitative readout. To effect gene expression disturbances time, we developed dynamic model for regulation in Arabidopsis thaliana. Model parameters were estimated based time-courses relevant genes, and consistent set times plants genetic backgrounds. Validation was performed by predicting changes level mutant backgrounds comparing these predictions with independent data, comparison predicted experimental several double mutants. Remarkably, predicts that disturbance particular has not necessarily largest impact directly connected genes. For example, SUPPRESSOR OF OVEREXPRESSION CONSTANS (SOC1) mutation larger APETALA1 (AP1), which regulated SOC1, compared its LEAFY (LFY) under direct control SOC1. This confirmed data. Another prediction involves importance cooperativity (AP1) LFY, supported evidence. Concluding, our enables address different one output, time.