Wheat is the crop most widely cultivated worldwide : 556 million tons of wheat are used for human food and animal feed. The production worldwide has not been increasing for ten years, while demand gets still more important. The program will investigate the influence of the vegetative and reproductive organ development on wheat Yield achievement as well as Genotype adaptation to environmental conditions. The studies will take into account the genetic factors and their interaction with the environment by doing multi-local field experimentations. The project is organised in three main workpackages: - Genetic analysis of the various components of yield will be made through QTL study, using a specific wheat population, derived from five cultivated inbred lines. Some fine phenotypic scorings of the plant vegetative growth and spike's development will lead to a better genetic understanding of yield's components. In a second subproject, a cross between two parents very contrasted for spike and tillering structuration will be used for genetic studies. Thirdly, the influence of the Ppd photoperiod genes on the plant development and the achievement of yield potential will be studied. - Candidate genes will be identified using the following methods: sequence data mining, gene mapping and collocation research. - Some association studies will be achieved for a number of candidates and known genes (Ppd, Vrn, …). We will then be able to validate their involvement in some traits of interest, or to better characterize their allelic effects. The deliverables expected from this project are (i) a better understanding of the genetic factors and their interactions which lead to the expression of a part of the yield potential, (ii) the identification of QTL and genes involved in the control of these traits and (iii) development of markers that will be helpful to better characterize the registered lines, and also helpful for breeding purposes

Several factors affect today a more extended use of microarrays for research and as a diagnosis tool. These factors are the experimental cost, the reproducibility of the measurements and the format of the analyses. This project aims at bringing solutions in these three domains by optimizing multiplexed analyses in order to reduce cost and enhance the number of samples treated simultaneously; by proposing new couples flurophores / slide surface in order to increase the signal precision and by developing new applications such as Comparative Genomic Hybridization (GGH) or Promoter Arrays to bring the plant microarray beyond transcriptome analyses. Altogether, these approaches will allow us to construct an optimized diagnostic tool based on 96 well microplate microarrays. This multidisciplinary project bring together biologists, chemists, physicists and mathematicians to develop innovative solutions for future application of DNA microarrays.

Wheat is the crop most widely cultivated worldwide: Each year, more than 550 million tons of wheat are used for human food and animal feed. If conventional breeding has allowed significant advances in terms of yield and grain quality, it will not be able to face the demands for increasing global crop production in a sustainable and environmental-friendly manner. Genomics holds the key to wheat improvement, through the development of new tools and methodologies to help breeders. In particular, the generation of molecular markers offers the potential to renew some breeding methodologies in diverse ways including Linkage disequilibrium (LD) mapping. LD analyses appear very interesting to the plant genetics community for its potential to use existing genetic resources collections in order to fine map quantitative trait loci (QTL), validate candidate genes and identify alleles of interest. Recently, the field of plant association genetics pioneered the use of a new type of association populations, designed to incorporate advantages of both linkage based and linkage disequilibrium based quantitative trait dissection approaches in association studies. These new strategies issued from animal breeding are a powerful tool for fast and large scale validation of candidate genes and precise QTL dissection in plants. The NEWNAM project proposes to investigate one of theses new strategies named NAM for Nested Association Mapping population, in order to create a new powerful resource of winter bread wheat for further use in genetic studies and breeding purposes. The NEWNAM project will be developed by 2 laboratories that are recognized leaders in wheat genomics and genotyping. It aims at providing a key strategy for future wheat research areas through the development of a new biological resource for the wheat community. This high resolution mapping resource will provide researchers and breeders with a tool for integrated research driven by the phenotype.

In the past 15 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including difficulty in gene identification and long time consuming methods. GAIN-SPEED aims at demonstrating in wheat the potential of combining genomics resources, particularly the chromosome’s first draft sequence, the next generation sequencing and array technologies and association mapping to develop an original strategy to accelerate the QTL cloning. This project is proposed with a companion project, 3Bseq, submitted to the Plant Genomics call 2009, whose objective is to produce a fully annotated genomic sequence of the largest bread wheat chromosome, the chromosome 3B, anchored to genetics maps. GAIN-SPEED will draw on the sequence produced to generate molecular markers on targeted regions to speed up marker assisted selection (MAS). This marker development will be processed using Nimblegen Sequence Capture technology that enables targeted sequencing of thousands of exons or contiguous genomic loci of up to 5Mb in a single experiment. That will allow us to develop large amount of SNP markers on gene rich regions containing putative candidate genes for our traits of interest. Using the next generation of genotyping platforms, these markers will be genotyped on an association panel that will help us to select more precisely the markers associated with the traits of interest and better define the zone carrying the QTL. The most associated SNP will be the start point to screen recombinant inbred lines and generate material useful for fine mapping approach. This project doesn’t aim to map based clone QTL but it will therefore lay the foundation of faster and more efficient MAS, through the fine mapping of important QTL, bringing together fundamental research developed in the companion project and industrial interests.

This project aims to set up a bioinformatic environment for the analysis of genetic and genomic data obtained both from cultivated plant species (such as Maize and Wheat) and model species (in particular Rice). It will concentrate on tools allowing to locate and identify genes of agronomical interest, either by direct studies on the species or through a comparison with a model genome which is better known. The strategy for identifying these genes will use lost of different approaches such as : - Integration of genetic maps and anchoring of BACs on these maps. - Integration, enhancement or adaptation of programs for the structural and functional annotation of all species. - Integration of public data as well as those produced within Genoplante I et II (genetic and physical maps, transcriptomics, proteomics, QTL, SNP, mutants, epistatic interactions between genes and QTL, metabolomics, networks). - Development of generic databases and tools for functional analysis. - Visualisation navigation through the data as an aid to the scientific research. The aims of the M2 project represent an equilibrium between the direct study of data on Maize, Wheat and Rice and the study of these data with the help of genome models (Arabidopsis and Rice).