Plant viruses are responsible for a significant proportion of crop diseases and are very difficult to combat due to the scarcity of effective countermeasures, placing them among the most important agricultural pathogens. Most emerging infectious diseases of plants are caused by viruses, being emergence provably favored by climate change, increased seasonal weather instability, and conditioned by intensive global trade. Viral diseases can affect food quality as well as reducing yields, yet quality is also affected by measures such as spraying with pesticides to kill off insect vectors. With no doubt, the best strategy for the control of plant viruses consist of the use of crop cultivars or varieties that are genetically resistant. Thus, introgressions of durable resistance to plant viruses into elite cultivars as well as the identification of new sources of resistance are major goals in plant research. About half of the ~200 known virus resistance genes in plants are recessively inherited, suggesting that recessive resistance is more common for viruses than for other plant pathogens. The use of such genes is a very important tool in breeding programs. Based on previous knowledge on recessive resistance to plant viruses generated by the participating teams, we propose the identification of new plant susceptibility factors whose modification would confer recessive virus resistance. We aim at transferring this knowledge to at least three important crop species: barley, tomato and melon.

Aims . Following its introduction into Europe in the late 15th early 16th centuries, maize developed unique adaptive features to environmental conditions. These traditional European accessions have proven extremely complementary to American cornbelt material in terms of heterosis, leading to the major success story of European hybrid maize. After comparison of all possible species, maize has proven to be the most efficient crop to produce high energy feed for animals through whole plant biomass harvested for silage conservation. This is to a large extent due to the unique efficiency of its C4 metabolism. for the same reason, maize also has been acknowledged as a possible solution for energy production for German regions with high water precipitation and 250.000 ha are already cultivated there, mostly with existing silage varieties. Further improvement of whole plant biomass production requires the identification of key alleles to optimise light interception and conversion into biomass, in particular through cold tolerance for early sowing, rapid leaf growth, and then conversion into biomass. Key alleles need also to be identified to monitor flowering time and plant maturity according to environmental factors and end product use, while maintain quality features. . Workplan To achieve this goal, the project associates a consortium of 4 major European based private companies and 10 public laboratories being major groups involved in maize genetics and physiology in Germany, France and Spain. These groups have complementary expertise in terms of advanced knowledge of maize genetic diversity, quantitative genetics and breeding methodology, material production using double haploid technology, phenotypic analysis of traits mentioned above, advanced technologies of polymorphism discovery and genotyping. Expertise and corresponding resources will be assembled into genetic approaches for deciphering the genetic determinism the traits of interest combining (i) connected multiparental linkage mapping designs and (ii) Linkage Disequilbrium (LD) mapping in optimised populations of diverse inbred lines. To do so, new polymorphisms and genotyping resources today not yet affordable to our community will be developed. Also populations of introgression materials will be prepared to validate and further investigate allelic effects and conduct fine mapping programs. The genetic variability obiomass accumulation will be analysed in phenotyping platforms and in the field. It will be dissected into mechanistic traits having a higher heritability, namely (i) leaf growth and its response to cold temperatures, studied either with high temporal definition for introgression lines or by daily 3D imaging in LD panels, (ii) radiation use efficiency and water use efficiency in the same platform, analysed daily. (iii) tolerance to cold temperatures. Biomass accumulation will be analysed in a network of field experiments comprising LD panels and multiparental crosses, with measurements during the crop cycle carried out by periodic measurements of biomass and of spectral reflectance of plant canopy. Specific attention will be paid in all cases to the representation of European maize diversity and its comparison with other origins presently investigated into US and international programs. Extension of the cooperation to Italian groups is intended to forman unprecedented European platform. A close connection will be established with the US community to conduct synergistic efforts, in particular to develop a common unique high density genotyping SNP platform. Expected results The project is built so as to provide directly applicable results in terms of alleles discovered at several key loci defining the desired ideotype, along with markers allowing a predictive inference within the main genetic groups considered for breeding and possibly at the species wide level. This is expected first for alleles making it possible to adjust the plant growth cycle and also for biomass composition. It will also settle a unique basis of knowledge regarding the variation of the traits of interest and provide protocols to evaluate these using advanced technologies. Also insight will be gained in the magnitude and organisation of Linkage Disequilibrium (LD) between and within genetic groups and its consequences for LD mapping. Specific attention will be paid to the organisation and durability of the access to the genetic resources assembled. Also key data obtained in the programs in terms of sequence polymorphism and high density genotyping will remain accessible to the partners of the project and a broader community through a database improved in the duration of the project. It is therefore expected that the resources and data produced will form the core of future cooperative efforts of partners