Molekulare Mechanismen der Datenintegration und Entscheidung zur Einleitung der Reproduktiven Phase in Pflanzen

Abstract

Within this joint project, we would like to address the question why plants show such a distinctive preference to combine a long-term winter memory and cues from photoperiod to track seasons. We will make use of the genetic model plant Arabidopsis, for which the molecular pathways involved in seasonal control have been best studied. Using mathematical modelling, we will simulate different molecular representations of flowering time control, in which either winter memory or changes in daytime length are required to precisely track season and quantify the ability of the different scenarios to correctly identify annual seasons. Additionally, we will investigate whether tracking of daytime length is an evolutionary stable strategy or can be invaded by winter memory. The experimental approach aims to implement a synthetic network in Arabidopsis that allows predicting season without vernalization requirement. This involves redirection of day length information to enter the epigenetic winter memory at the FLC Locus or bypasses the requirement for FLC by directly altering the balance of florigen and anti-florigen expression. The synthetic approach will be assisted by mathematical modelling to predict the minimum requirements needed to circumvent vernalization. Additionally, we will quantify information integration and decision-making at FT by genetic manipulations.