BLOOM-NET

从营养发育向生殖发育的转变具有根本的农业重要性，因为花卉对育种者和装饰业是必不可少的，也是果实和种子形成的先决条件，而果实和种子是人类和动物食物的主要来源。这一重要性导致了对花的过渡的广泛研究，并确定了大多数关键的调节因子。目前的挑战是理解这些因素如何共同作用，将各种外部和内部信号整合成一个明显简单的输出：在最佳时间形成花朵。这个项目的总体目标是确定在顶端分生组织(SAM)中作用的复杂调控网络，以调控花过渡到开花的时间，并模拟该网络在花过渡期间的数量和动态变化。为此，我们将重点介绍属于MADS-box转录因子家族的一组重要的关键调控因子，它们可以作为花转换的抑制者或诱导者。先进的基因组工具，如全基因组染色质免疫沉淀(CHIP)、高通量Illumina/Solexa测序和表面等离子体共振(SPR)，将被应用于产生全面和定量的数据集，涉及MADS-box蛋白表达水平、表型输出、体内靶基因启动子占有率及其蛋白-蛋白质相互作用亲和力。此外，SAM转录组将在花诱导的非常早期阶段进行研究，并与芯片数据相关联。定量数据的产生将使我们能够将花期的数学模型参数化，这将导致新的假设，随后可以进行测试和实验验证和完善。为此，我们组建了一个由四个不同的湿实验室研究小组和一个生物信息学小组组成的联盟，他们将密切合作，以实现该方案的目标。这些团队要么是开花研究方面的专家，要么是其中一项拟议技术的先驱。将定量数据纳入调控网络模型将使我们深入了解一般的转录控制，特别是花计时背后的复杂调控网络。此外，我们预计这一结果将引起普遍关注，并为育种者和植物种植者提供未来的应用。

The transition from vegetative to generative development is of fundamental agricultural importance, because flowers are essential for breeders and the ornamental industry and are prerequisites for fruit and seed formation, which form the major source of human and animal food. This importance has resulted in the floral transition being extensively studied, and most key regulators have been identified. The current challenge is to understand how these factors act together to integrate the various external and internal signals into one apparently simple output: the formation of flowers at the optimal time. The overall aim of this project is to define the complex regulatory network that acts in the shoot apical meristem (SAM) to regulate the time of the transition to flowering, and to model quantitative and dynamic changes in this network during the floral transition. For this purpose, we will focus on an important set of key regulators that belong to the MADS-box transcription factor family, and that function either as repressors or inducers of the floral transition. Sophisticated genomic tools, such as genome-wide Chromatin Immunoprecipitation (ChIP), high-throughput Illumina/Solexa sequencing, and Surface Plasmon Resonance (SPR), will be applied to generate comprehensive and quantitative data sets, concerning MADS-box protein expression levels, phenotypic output, in vivo target gene promoter occupancy and their protein-protein interaction affinities. Furthermore, the SAM transcriptome will be investigated during the very early stages of floral induction and correlated with the ChIP data. The generation of quantitative data will allow us to parameterize a mathematical model for floral timing, which will lead to novel hypotheses that subsequently can be tested and experimentally validated and refined. To this end, we have compiled a consortium comprising of four different wet-lab research groups and one bioinformatics group, who will collaborate closely to meet the objectives of the programme. The groups are either experts in flowering research, or pioneers in one of the proposed technologies. The incorporation of quantitative data into a regulatory network model will give an insight into general transcriptional control and in particular into the complex regulatory network behind floral timing. Furthermore, we foresee that the outcome will be of general interest and offer applications for breeders and plant growers in the future.