SPP 1530: Flowering Time Control - from Natural Variation to Crop Improvement

Work program

Guiding Principles

 

The SPP is structured into 5 work packages (WP).

 

‘Omics’-based technologies and data mining for identifying and characterizing the network of FTi regulators and their targets are clearly preferred.

Also the relevance of endogenous and exogenous factors shall be elucidated and their interaction with regulatory network shall be elaborated.

These different approaches require an interdisciplinary network of research groups which must be clearly outlined in the project proposal.  Projects crossing the borders between different fields of research will be preferred. These are all aspects of modern plant biology including molecular genetics, genome research, breeding research, plant physiology, and bioinformatics and biostatistics. Special emphasis will be given to those projects which have a focus on genetic improvement of cultivated plants like agricultural and horticultural crop plants, ornamentals and woody perennials. Also model plant projects shall be funded if the outcome of their research will have a clearly foreseeable impact on cultivated plants. 

 

Constraints

 

The priority program does not include studies dealing with floral organ development only without regard to the aforementioned regulatory networks. Also basic studies on FTi regulation in models not related to application in cultivated plants is excluded. On the other hand, projects only relying on traditional (phenotypic) selection and breeding approaches will not get priority as well as field or purely agronomic studies without genetic or ‘omics’-based approaches. Research exclusively focusing on epigenetic regulation of FTi or senescence without relation to FTi are not part of this program.

 

 Integrative projects and joint experiments

 

The conservation of FTi regulators and networks across species borders and the availability of vast genomic and other sequence and expression resources create a unique opportunity for joint interdisciplinary experiments between basic and applied researchers, geneticists and bioinformaticians, physiologists and breeders. The ambitious goals (see “Strategic goals”) can only be reached by a collaborative approach in the frame of a SPP. A number of joint initiatives are expected. These are either central activities (see “Duration and timeline”) or bilateral projects focusing on common triggers between crops and models. Given the hypothesis of general flowering gene regulation networks a number of projects shall focus on sequence based identification and verification of FTi regulators and comparing genetic networks in crops using already established information from models. Joint activities are expected for the comparative analysis of metabolic regulators in different plant species and for establishing databases). Furthermore, general mechanisms of phenological development across species borders shall be pursued.

 

Flowering time regulation in perennials is of major importance during this SPP. Thus joint experiments are encouraged between perennial model and crop projects. Likewise, the relationship between FTi and stress response shall be jointly worked out in models and crops.

Integrative projects will be focused on bioinformatics, transcriptomics and mutant detection. The process of acquisition genotype and phenotype data and utilization thereof will be accompanied by bioinformatics tools. These tools are required in order to store, visualize, process, and statistically interpret the collected ‘omics’ data from testing flowering parameters under different environmental conditions. For this, existing freely available databases and data mining software like MAPMAN, GERMINATE, and Phenom Networks will be used. The new sequencing technologies offer the opportunity for comprehensive analyses of the transcriptome. Integrative projects shall decipher the transcriptional network underlying FTi regulation using digital gene expression techniques in combination with next generation sequencing. Hence, databases and algorithms for storing and analyzing these data shall be developed (goal No. 7). Emphasis shall be put on the development of integrative analysis approaches such as the analysis of expression data in the context of sequence data including segmental duplications and copy-number variations, ChIP-seq data, proteomics, or metabolomics data. Likewise, novel approaches for the analysis of expression data from different tissues, different time points, different ecotypes, and different mutants in a holistic manner (comparative transcriptomics) shall be developed. The availability of complete genomic sequences from models and a number of crops (e.g. legumes, grapevine, apple, sugar beet, or oilseed rape) will create unique opportunities for sequence based gene detection in crops and deep transcriptome sequencing. A transcript database shall be established as a unique resource for detecting new FTi regulators including antisense mechanisms. Novel sequence based mutant detection platforms shall be established for fast identification of novel sequence variants and their phenotypes. A close interaction with the SPP1395 “Information and communication theory in molecular biology” is desirable, as several of the algorithms developed there are of direct relevance for this SPP.
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