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BLOOM-NET

布卢姆网

基本信息

批准号：
BB/G024995/1
负责人：
Brendan Davies
金额：
$ 36.27万
依托单位：
University of Leeds
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FG024995%2F1
关键词：
BLOOM NET

项目摘要

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.

从营养向生殖发育的转变具有根本的农业重要性，因为花对于育种者和观赏产业是必不可少的，并且是果实和种子形成的先决条件，而果实和种子形成是人类和动物食物的主要来源。这种重要性导致了花的转变被广泛研究，大多数关键的调节剂已经确定。目前的挑战是了解这些因素如何共同作用，将各种外部和内部信号整合到一个看似简单的输出中：在最佳时间形成花朵。该项目的总体目标是定义复杂的调控网络，在拍摄顶端分生组织（SAM）的行为，以调节开花的过渡时间，并在花的过渡过程中，在这个网络的定量和动态变化的模型。为了这个目的，我们将集中在一组重要的关键监管机构，属于MADS盒转录因子家族，功能无论是作为抑制剂或诱导剂的花过渡。复杂的基因组工具，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），将用于生成全面和定量的数据集，涉及MADS盒蛋白表达水平，表型输出，体内靶基因启动子占用及其蛋白质-蛋白质相互作用亲和力。此外，SAM转录组将在成花诱导的非常早期阶段进行研究，并与ChIP数据相关联。定量数据的产生将使我们能够参数化开花时间的数学模型，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，以实现该计划的目标。这些小组要么是开花研究的专家，要么是某项拟议技术的先驱。将定量数据纳入调控网络模型将使人们深入了解一般的转录控制，特别是复杂的调控网络背后的开花时间。此外，我们预计该成果将受到普遍关注，并在未来为育种者和植物种植者提供应用。