Nathalie Mandonnet

Team Ceresita

Which animal do farmers need for tropical mixed farming systems in the Caribbean?

 (FAO 2008)(FAO 2010)

Three principles for efficient livestock production in the tropics

Based on the observation and evaluation of mixed farming systems (MFS) in the Caribbean:

On the farm,

1.

  Give priority to food on feed 2. Promote the right animal at the right place 3. Favour farmers' wills and skills Ressources alimentaires locales Crédit Photo : M .Mahieu 1. Optimize a human food system in which the animal protein is only one component • Dual food crop plants (eg bananas, sweet potatoes, cassava, cereal, peas…), • Recycle crops co-products as feed and energy. 2. Choose adapted plant resources to the agro-pedo-climatic environment of the farm • Evaluation of the local biodiversity (from dual food to legume fodder trees) Coproducts and non conventional plants user guides Traditionnal creole garden Priority to food on feed 3. Match the animal with the plant resources available on the farm • Account for differential physiological abilities between ruminants and monogastric • Ruminant : development of non usable lands, low feed conversion and greenhouse gaz production domestication of natural process with smart and robust technologies • Single cell protein production (algae, fungi, basteria) for livestock protein supplementation • Methane fermentation and lactic acid fermentation to produce energy while allowing effluent depollution, mitigation of greenhouse gas, and forage preservation. Coproducts and non conventional plants user guides Traditionnal creole garden The right animal at the right place 1. Prioritize low-input local adapted breeds (instead of high-input/ specialized exotic breeds) Constraints: Variability of amount and quality of feed, biotic and abiotic stress • Optimize responses laws (production and adaptation) of conventional livestock • Enhance the potential provided by the non-conventional animals Mixed farming INRA Gardel Crédit : M.Mahieu

issues of agriculture in the Global South

	• World population will
	reach 9billions by 2050
	+50% in Global South
	• Limited increase of arable
	land surface
	 Decreased land
	availability for crops
	and livestock
	production /inhab
	• Crucial need of increased
	agriculture efficiency to
	reach food sovereignty



Major

Acknowledgments to the team And Thank you for your attention!

The right animal at the right place 2. Enhance diversity within the flock (genetic, physiological status) to "empower" the existing diversity of the system • Resilience: define and design the animal/system able to make/allow the right compromise under stress -Ex: genetic control of nutrient allocation in pig under heat stress, importance of production and ecosystemic services integration in resilience of MFS

• Efficiency: multicriteria evaluation and optimization at the A/P/S levels -Ex: feeding strategies, integrated control of animal health, co-conception of MFS -La recherche prend ses responsabilités


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text:
Claire Mosnier

published or not. The documents may come     Suckler beef systems in France: evolution, future prospects and challenges regarding GHG emissions

Suckler beef systems in France: evolution, future prospects and challenges regarding GHG emissions.

Suckler beef systems are an important feature of French agriculture. Indeed the 4 millions French suckler cows 1 represent more than one third of all European suckler cows and supply around 65% of the beef production in France (France is self sufficient in beef meat). 70% of the 97000 1 suckler cow farms sell culled cows and weanlings. Around one million weanlings are exported from France each year, mainly for a finishing in the Po Valley, in Italy. The national beef herd is composed of various pure breeds. The Charolais breed accounts for nearly half of Suckler Cows 1 . Next are Limousin (23%), Blonde d'Aquitaine (12%), Salers (5%) and Aubrac (4%) 1 . These breeds are maintained as regional particularities and are an asset for marketing. More than 80% of animal diets come from grass grazed (50%) or harvested 1 . Consequently, these systems predominate in grassland areas and are located mainly in the Massif Central (43% of suckler cows in 2011: source BDNI). The French beef sector plays a key role in rural development and tourism of least favoured areas such Massif Central and helps in maintaining these large areas under grassland which favours biodiversity, limits pollution and erosion and stores carbon.

The prospects regarding suckler cow outlets are uncertain. The demand for meat is expected to increase in the long run as the world's population increases (over 9 billion in 2040) but for the next decade, the drop in demand for weanlings from Italy (currently, 70% of weanlings are exported to Italy) and increased competition from Eastern European countries are likely to reduce the export market for weanlings. In addition, the number of suckler cows doubled between 1984 and 2000, after the introduction of milk quotas. With the abolition of milk quotas, the contrary process might be observed. Low income and high public support dependency (net income: 13k€/ worker unit, subsidies: 32 k€/ worker unit based on 2013 FADN data) are also important weaknesses of these systems. To keep or improve their market share, suckler cows farms would need improve their competitiveness and profitability. Environmental concerns are growing. A major issue is climate change. Since the creation of the Intergovernmental Panel on Climate Change (IPCC) in 1988, number of scientific reports have alerted on the major role played by greenhouse gases (GHG) released in the atmosphere on global warming. The objective of the French government is to reduce by 75% GHG emissions in 2050 relative to 1990. Ruminant livestock systems are major producers of GHG emissions including methane. According to the Citepa (2013), the cattle sector accounts for 60% of the French agricultural sector emissions, i.e. 10% of national emissions.

To improve farm income, competitiveness, and to reduce GHG emissions, the efficiency of the production process should be improved. However, over the last decades, the reduction of GHG emissions per kg of meat produced has been small. Veysset et al. (2014a) and Dakpo et al (forthcoming) analysed the evolution of production efficiency at farm level based on a panel of farms located in the North of Massif Central, collected over the period 1980-2012 (>3000 observations). They emphasized that the production of meat per farm have more than doubled while the number of worker units per farm remained constant. This gain was obtained thanks to an increase in herd size and forage area per farm (+180%) but above all thanks to an 1 Ellies MP, Papillon S, 2014, Les filières animales françaises : Chiffres-clés, Coll. Synthèse Agricole Broché, 136 p increase in intermediate consumptions (+240%). These intermediate consumptions encompass the costs of concentrate feed and purchased fodder, materiel and building depreciations, fertilizers, fuel, services etc. An important substitution between labour and intermediate consumption occurred (more machinery and equipments, simplified herd feeding practices etc.). Farm size per worker unit has indeed long been a key determinant of farm income, above all by the subsidy income recoverable (Veysset et al., 2014b). However, this correlation has become weaker in recent years resulting from higher input prices, increasing costs from machinery and fuel and a slight reduction of cow reproductive performance. Farmers have now higher incentive to improve efficiency of intermediate consumption. GHG emissions per kg of meat has decreased as meat production per livestock unit increased: from 16.1kg CO 2 eq/kg meat (live) without accounting for carbon storage in 1981 to 14.9kg in 1990, to 14.4 kg in 2013. 60% comes from CH 4 (80% enteric fermentation, 20% dejections), 25 % from N 2 O (fertilization), 15% from CO 2 (fossil energy and indirect emissions) [START_REF] Veysset | Variability in greenhouse gas emissions, fossil energy consumption and farm economics in suckler beef production in 59 French farms[END_REF]. To simultaneously account for the different production factors and products (meat and GHG), a data envelopment analysis was performed. Dakpo et al (forthcoming) show that for a given combination of production factors, eco-efficiency had increased slightly (+4%) over the period 1980-2013. This gain is explained by the increase in meat production per livestock unit. Low production efficiency could be explained by risk management since farmers could opt for use less efficient but more resilient production options. An analysis of 1,535 farm observations over the period 2000-2009[START_REF] Mosnier | Impacts des aléas climatiques en élevages bovin et ovin allaitants et demande de couverture assurantielle[END_REF] emphasize for instance that the current production systems (economic results) are resistant to variation of grass harvested per livestock unit above -20% relative to average values and that lower level of meat production per hectare reduce gross margin variability [START_REF] Mosnier | Evolution and sensitivity to hazards of technical and economic indicators of suckler cow farms according to different production systems: A panel data analysis of 55 French Charolais farms from 1987 to 2007[END_REF]; INRA Reasearch are carried out at different levels to find out solutions that would reduce cattle GHG emissions. First methanogenesis linked to enteric fermentation is studied in vitro thanks to molecular biology. [START_REF] Popova | Effect of fibre-and starch-rich finishing diets on methanogenic Archaea diversity and activity in the rumen of feedlot bulls[END_REF] demonstrate for instance that defaunation or flax supplementation reduce the methanogen activity of microbes. Experimental facilities have been developed to measure methane emission in vivo (SF6 tracer techniques for outdoor measurements, special rooms for indoor measurements). Accessible indicators of methane production are tested such as milk fatty acids. In the case of flax supplementation, some fatty acid of milk predict accurately CH4 emissions (Ferlay et al 2009). To strengthen research on the identification and validation of indicators of enteric methane production in ruminants, an innovative approach for the co-construction of a research program between INRA and ten private partners is built up. Emissions have to be reduced at the animal level but also at higher levels taking into indirect emissions. Thanks to life cycle assessment, Nguyen et al, 2010 demonstrate for instance that the effect of flax supplementation on GHG emission is not significant anymore. Within the Gesebov project coordinated by Idele (livestock institute), a bioeconomic farm model is developed (Mosnier et al, forthcoming) to run prospective scenarios regarding animal and GHG production by 2035 for main cattle French farm types.


Maryline Filippi
email: maryline.filippi@agroparistech.fr

Intangible investments in wine co-ops: catalyzers between governance and performance

Introduction / Context

Cooperatives:owner-members enterprises coming from poverty, crisis and reaction against market disaster, especially in agricultural sector French wine co-ops are major operators in the wine sector -LR ones are the most numerous, and also frequently the smallest ones

We aim to analyse the determinants of their competitiveness. We also study to what extent intangible investments interact with co-op governance and performance -skills (education as well as human capital) -brands, -normalizations and certifications, -subsidiaries, including financial participations.

Informal bodies, cognition and partnerships aspects allow disembeddeness.

Intangible investments are powerful tools used in order to establish collective commitments. They enable to reduce asymmetric information, asymmetric knowledge, and to improve collective action.

In fact, intangible investments act as a "catalyzer" for triggering governance effects on financial performance  it paves the way for future researches.

2

  Ways of cooperative governance: in transition because of increasing collaborative and knowledge based-economy Cooperatives governance: different faces and multi-paradigmatic conceptual framework (Cornforth, 2004) Three main levels: disciplinary, partnership and cognitive dimensions (Saïsset, 2016) -But partnership and cognitive ones appear as the most influent on cooperative performance (Saïsset et al., 2016) on intangible investmentsknowledge sharing is crucial for going ahead and invest in marketing Test of H3 : Intangible investments has a mediator effect on the link between governance and performance H3 is validated -Moderator effect of II si real and important Cognition is crucial, impulsing intangible and financial performance Conclusion 15 Results confirm the major part of our hypothesis Results underline the interest in combining the four main categories of intangible investments:

Intangible investments in wine co-ops: catalyzers between governance and performance -AAWE 2016 -Bordeaux

Intangible investments in wine co-ops: catalyzers between governance and performance -AAWE 2016 -BordeauxResults and discussion

Role of intangible

 Demotes-Mainard (2003): intangible = « Invisible man » difficult to define Investor vision = human capital, organisationnal capital, customers and network capital Dynamics and cumulative effects of previous intangible investments ( Arrighetti et al., 2014)


domain: sdv info

text:
Yoannah François

Caroline Molette

Alain Vignal

Stéphane Davail

Christel C Marie-Etancelin

Detection Of Pleiotropic QTL Related To Protein Expression And Foie Gras Quality Traits

Keywords:

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In France, 95% of foie gras is produced by mule ducks, which are interspecific hybrids issued from the cross between a common female duck (Anas Platyrhynchos) and a Muscovy drake (Cairina Moschata). The main objective of the industry is to improve the foie gras quality. A first study for estimating the influence of the duck genome expression on foie gras quality traits identified several QTL (Kileh-Wais et al. (2013)). We now propose to go further by exploring the influence of the protein expression levels. The purpose is to identify proteomic QTL (pQTL) influencing liver protein expression and to find pleiotropic QTL between phenotypes and proteins.

Material and methods

So as to reduce the number of animals to analyze by proteomics, our pQTL backcross design was a reduction of the one used for all mule ducks traits (Kileh-Wais et al. (2013)). This cross was based on 7 F1 families with a total of 382 back-cross (BC) female common ducks. These BC females were progeny-tested by measuring traits in their mule duck sons and genotyped with 102 microsatellite markers associated in 17 linkage groups (LG) for QTL detections. The pQTL design focused on 3 of these families for which major QTL for liver quality traits had been detected (François et al. (2013)).

Animal Design. This optimized design is thus composed of 3 F1 sires, 98 BC pekin females and 294 grand-sire mule ducks (figure 1). The 3 F1 drakes are products of a cross between 2 common duck parental lines (the heavy pekin INRA37 and the light Kaiya INRA444). These 3 F1 sires were backcrossed to 20 INRA444 female common ducks to produce BC female common ducks. To estimate their values, these BC were crossed with 23 Muscovy drakes to produce the mule ducks. To minimize proteomics work and to keep the design balanced, exactly 3 mule ducks sons per dam were kept for analysis, that is to say a total of 294 animals. Mule ducks were bred from 0 to 12 weeks of age, followed by an overfeeding period of 12 days. After slaughter, liver samples were collected and numerous liver phenotypic traits were measured.

Genotyping and genetic map. All the common ducks of this design had been genotyped with 91 microsatellites markers (Kileh-Wais et al. (2013)). Only the 2 linkage groups -LG2c and LG9 -for which interesting traits segregating in the 3 families considered here, could be analyzed (figure 2). Data recording. Five liver quality traits were measured on the 294 duck livers: the liver weight (LW), the melting rate (MR), corresponding to the fat loss during cooking, the protein and lipid percent in dry liver (LprotDc and LlipDc) and the liver redness (La). Liver soluble proteins were extracted from liver samples and separated using bi-dimensional gel electrophoresis. Computational analyzes of the 326 protein spots present on the gels produced level values for each spot and each 294 sample.

QTL detections. QTL and pQTL detections were performed on the 98 females BC from the optimized design, their performances being the mean value of that of their sons. Linkage analysis was performed according to the interval mapping method (Lander and Botstein (1989)) with the QTLMap software (Elsen et al. (1999)) and the empirical chromosome-wide significance (CWS) level was estimated with 1,000 within-family permutations. First, single trait QTL and pQTL detections were carried out for the liver quality traits and for each of the 326 protein spots, respectively. Detections of multi-trait QTL (mQTL) were then performed by combining each pQTL with each of the significant quality phenotype QTL, in order to identify pleiotropic QTL.

Results

Single trait QTL. A total of 8 QTL -3 on

LG2c and 5 on LG9 -significant at 5% CWS and related to foie gras quality traits, were identified (table 1), confirming the results of Kileh-Wais et al. (2013). The 3 strongest QTL were identified on LG9 for LprotDc (1% CWS) and LW and LlipDc (0.5% CWS). Twenty-three pQTL -15 on LG2c and 8 on LG9 -significant at 5% CWS, were detected for 22 out of the 326 spots tested (figure 3). As most of the 326 protein spots present on the gel have not yet been identified, only 8 out of the 22 significant pQTL are known accurately to date and we will focus analyses on them (table 1). Each LG counted 4 QTL related to the following proteins: Peroxiredoxin (PRDX6), Triose Phosphate Isomerase (TPI), destrin (DSTN), and alpha-enolase (ENO1 (1)) on LG2c and alpha-enolase (ENO1 (2) and ( 3)), NADH dehydrogenase iron-sulfur protein 3 (NDUFS3) and Proteasome Subunit alpha 1 (PSMA1) on LG9. The most significant pQTL was for TPI on LG2c (0.5% CWS).

Multi-traits QTL. For each LG, each pQTL was combined to each of the phenotypes presenting significant QTL. Twenty combinations (4 pQTL x 5 phenotypes) were tested for LG9 and 12 (4pQTL x 3 phenotypes) for LG2c. These all gave rise to significant mQTL at 5% CWS. The association of two traits never decrease the mQTL p-value compared to single QTL or pQTL. For 14 combinations the threshold reached by the mQTL is higher than the best of the 2 single QTL/pQTL (table 2) i.e. on LG9, the association between PSMA1 and La gives a very significant mQTL at 0.5% CWS, whereas both single QTL and pQTL only reached 5% CWS. On LG2c, the association between LlipDc and the proteins gave rise to 4 strong mQTL (0.5% CWS with PRDX6, DSTN and ENO1 and 0.1% CWS with TPI). On LG2c, all mQTL for ENO1 are stronger than the single QTL (0.5% CWS). On LG9, 4 mQTL for ENO1 follow the same trend (with MR and LprotDc).

Discussion

LG2c and LG9 segregated for 15 QTL related to "foie gras" quality in the first study using all 7 backcross families (Kileh-Wais et al. ( 2013)). Our reduction to 3 families with 3 mule ducks per backcross common female duck still allowed us to detect 12 out of the 15 QTL. Moreover, 23 pQTL were also identified for 22 protein spots. The fact that these pQTL allow the detection of very significant mQTL when combined with LlipDc, MR or LprotDc, suggests that genes involved in or regulating the lipid and/or glucose metabolism reside in these locations, especially on L2c. On LG9 there is a clear pleiotropic effect between MR and ENO1 with both single pQTL and QTL only at 5% CWS and the mQTL reaching 0.5% CWS. Among the spots identified, TPI, ENO1 (both enzymes of the glycolysis) and PSMA1 (a subunit of the proteasome) had already been highlighted as linked to the variability of the melting rate (Theron et al. (2011)). Moreover, François et al. (submitted paper) showed that ENO1 and PRDX6 (a stress response protein) were linked to liver weight and to liver protein rate variability. Even if these results comfort our hypothesis, the mQTL between DSTN (involved in actin de-polymerization) and LlipDc on LG9 bring a new hypothesis on a link between LlipDc and the hepatocyte structure.

Conclusion

The protein spots identification to come will probably help in indicating the pathways concerned by the QTL. Moreover, our LG are small (1cM for LG2c and 20 cM for LG9) so the QTL positions are not accurate enough. In order to bring precision on the location, the same QTL, pQTL and mQTL detections are about to be performed on a genetic map composed of the these microsatellite markers and of SNP.

Literature cited

Elsen, J.M., Mangin, B., Goffinet, B. et al. (1999).

Genet. Sel. Evol. 31:213-224. François, Y., Marie-Etancelin, C., Molette, C. et al. (2013). 10 e JRAPFG, 1-5. Kileh-Wais, M., Elsen, J.M., Vignal, A. et al. (2013). J.

Anim. Sci. 91:588-604. Lander, E.S. and Botstein, D. (1989). Genetics 121:185-199. Theron, L., Fernandez, X., Marty-Gasset, N. et al.

(2011). J. Agric. Food, Chem. 59: 12617-12628. LG2c

LG9

Figure 1 :Figure 2 :Figure 3 :

 123 Figure 1: Backcross design and offspring testing for pQTL detections in the common duck

  MR=Melting rate, LlipDc=Dry liver lipid content, LprotDc=Dry liver protein content, La = Liver redness, LW = Liver Weight, PRDX6 = Peroxiredoxin 6, TPI = TriosePhosphate Isomerase, DSTN = Destrin, ENO1 = α-enolase, NDUFS3=NADH dehydrogenase iron-sulfur protein 3, PSMA1 = Proteasome subunit alpha. Stars next to the names of the traits indicate the significance of their single QTL or pQTL. All multi-trait QTL are significant at least at 5% Chromosome Wide Significance (CWS). Values presented correspond to the multi-trait QTL whose reached threshold is higher than the best of the 2 single QTL/pQTL. *: 5% CWS; **: 1% CWS; ***: 0.5% CWS; ****: 0.01 CWS.

Table 1 : QTL and pQTL identified on the linkage groups 2c and

 1

	9

Table 2 : LRT and threshold reached by the pleiotropic QTL in each linkage group (LG)

 2

	LG2c


Thierry Tribout

Marine Barbat

Armelle Gion

Amandine Launay

Rachel Lefebvre

Anne Barbat

Mekki Boussaha

Pascal Croiseau

Marie-Pierre Sanchez

Sebastien Fritz

Using whole genome sequences to identify QTL for udder health and morphology in French dairy cattle

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Using whole genome sequences to identify QTL for udder health and morphology in French dairy cattle T. Tribout 1 , M. Barbat 1,2 , A. Govignon-Gion 1,3 , A. Launay 3 , R. Lefebvre 1 , A. Barbat 1 , M. Boussaha 1 , P. Croiseau 1 , M.P. Sanchez 1 , S. Fritz 1,2 1 GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France; 2 Allice, 75012 Paris, France; 3 Idele, 75012 Paris, France.

Genome-wide association studies (GWAS) at the sequence level were performed in Montbéliarde (MO), Normande (NO) and Holstein (HO) breeds for somatic cells counts, clinical mastitis scores, and 9 to 11 udder morphology traits by breed. The number of bulls considered by trait varied from 1,857 to 2,515 in MO breed, from 624 to 2,203 in NO breed, and from 4,959 to 6,321 in HO breed. The considered response variables were the bulls' daughter yield deviations (DYD), derived from the national genetic evaluations. The DYD reliability of all the bulls considered in the analyses exceeded 0.2 (clinical mastitis) or 0.5 (other traits). Genotypes of the bulls for 27,754,235 sequence variants were imputed in 2 steps, using FImpute software: first from 50K level to HD level using 522 MO, 546 NO, and 776 HO HD genotyped bulls as a reference, and then to the sequence level using 1,147 sequenced bulls from the 1,000 bull genomes project. GWAS were done independently within each breed and for each trait, using GCTA software, accounting for the population structure through a HD-based genomic relationship matrix. A total of 49, 18 and 47 significant QTL (-logP>6) were detected in MO, NO and HO breeds, respectively. Among them, 10, 2 and 12 QTL in MO, NO and HO breeds, respectively, were highly significant (-logP>9). Most of the QTL affected only 1 trait in 1 breed, but locations on chromosomes 4, 6, 17, 19 and 29 showed significant results for 2 to 5 traits within a breed and/or similar traits in 2 breeds. Multi-markers analyses (BayesC method) were realized on targeted regions around the QTL (from 2 to 9 Mb length) using GS3 software, to reduce the effect of long distance linkage disequilibrium and to narrow the location of the potential causative mutations. Combining these results with functional annotations led us to several good candidate genes, such as RBM19, GC, NPFFR2, RASSF6 and LIFR. Authors acknowledge the financial support from APIS-GENE and the contribution of the 1,000 bull genomes consortium.


est destinée au dépôt

Towards the identification of gene candiates for maternal effects on weaning weight in six beef cattle breeds

Florence Phocas, Marine Barbat, Mekki Boussaha, Dominique Rocha

To cite this version:

  Towards the identification of gene candidates for maternal effects on weaning weight in six beef cattle breeds Phocas F.,Barbat M., Boussaha M., Rocha D. Aquitaine, 299 Aubrac, 263 Parthenais and 198 Salers animals, that were mainly well proven bulls. SNPs were mapped onto the UMD 3.1 bovine whole-genome sequence assembly. In total 706 QTLs were identified across the six breeds, number ranging from 56 QTLs in Limousin to 275 QTLs in Charolais cattle. Only 30% of those QTLs were detected at least in 2 breeds and never in more than 4 out of the 6 breeds analyzed. Most of the main QTLs were breed specific. For instance, among the 26 largest QTLs found in Charolais (Bayes factor above 400), only 8 QTLs were detected in another breed; including 3 detected in three different breeds. Only one major QTL in Charolais breed was evidenced as a major QTL in another breed (Salers) and contains IGF-I as a very likely causative candidate gene. In total, 50 QTLs regions were fine mapped with 14 harbouring only a single candidate gene, 10 with only 2 genes and 8 with only 3 candidate genes.

	Detection of quantitative trait loci was carried out for maternal effect on weaning
	weight in French Charolais, Limousin, Blonde d'Aquitaine, Partenaise, Aubrac and
	Salers breeds using a Bayesian Variable Selection method.
	A total of 2,540 animals were genotyped (87%) or imputed (13%) for 706,791 SNPs
	located on the Illumina BovineHD BeadChip®. These samples included 795
	Charolais, 601 Limousin, 387 Blonde d'


L E Gouis

Oral Communication Abstract -5.01 QTL ANALYSES FOR NITROGEN USE AND GRAIN PROTEIN IN BREAD WHEAT

Keywords: grain protein composition, grain protein deviation, nitrogen deficiency, triticum aestivum L

The cost of nitrogen fertilization and growing environmental concerns tend to limit nitrogen application in a context of expanding world demand for cereal production and quality. Higher nitrogen use efficiency for grain yield, protein concentration and composition is then becoming an important objective for breeders. Phenotyping for these traits are however time and money consuming. Genetic progress may then depend on the development of accurate phenotyping methods and identification of molecular markers associated to chromosomal regions of interest.

To this purpose, different panels of bread wheats were used to assess the genetic diversity, the genetic progress and detect QTL. The first panel is composed of about 200 accessions representing the worldwide variability. It was both phenotyped for adaptation to N stress and for grain protein concentration and composition in multi-environment trials as a combination of different site x season and two nitrogen levels. Association genetics using about 1000 markers enable to detect regions associated to the N allocation to the different seed storage proteins (quantity of gliadin and glutenin) in different environments. One of the main result indicates that the genetic regions controlling the glutenin and gliadin compositions are mostly distinct from each other. The second panel that contains about 225 wheat elite varieties registered during the last 25 years was also experimented in multi-environment trials. Measurements involved grain yield, yield components and nitrogen contents at harvest. The genetic progress was assessed on genotypic additive value revealing significant progresses on grain yield, remobilization and nitrogen use efficiency. The nitrogen level x genotype interaction was significant, with a higher genetic progress for nitrogen use efficiency at low nitrogen attesting an improvement in yield stability. This phenotyping results were then used in a genome wide association study using more than 23k mapped SNP revealing several associated regions. The third panel that partly overlaps the second one was genotyped using a 420k Axiom array (TaBW420k) developed within the BreedWheat project. Genome wide association analysis is ongoing to identify genomic areas linked to nitrogen use efficiency. The comparison of regions identified in the different association studies will enable the identification of robust regions of interest. These results will be used to identify potential target regions for fine mapping and to develop informative markers to facilitate the selection for higher nitrogen use efficiency for grain yield and proteins.


Janejira Duangjit

Mathilde Causse

Christopher Sauvage

Effect of shrinkage on prediction accuracy of methionine and proline fruit contentsin a broad-based tomato population

Keywords: genomic selection, predicted breeding value, shrinkage intensity

Genomic selection is a promising marker assisted selection based application for quantitative traits improvement. In this study, the genomic estimated breeding values (GEBVs) were estimated by the ridgeregression best linear unbiased prediction (rrBLUP) statistical model with a training set of 122 accessions (122/163 -75%) from an available dataset representing a broad-based tomato population. Methionine and proline contents were randomly picked as representative of low heritability (h 2 <0.5) and high heritability (h 2 >0.7) metabolomics traits, respectively. The goals are to minimize mean-squared error (MSE) and to see the potential of using low marker density (250≤m≤1500). Results showed that shrinkage intensity was affected by the number of markers used in the model; and it ranged from 1% to 7% (the lower number of markers, the higher shrinkage intensity). In this tomato population, accuracies predicted by shrinked approach revealed benefit of shrinkage over non-shrinked approach, in methionine but not proline fruit contents, when used small number of marker (m=250). This suggests that shrinkage should be applied to low heritability traits to improve prediction accuracy in a board-based tomato population.

INTRODUCTION

Genomic selection (GS) is an approach utilizing information from molecular markers covering the whole genome of organisms. The aim of this technique is to shorten the selection by using genotypic information to predict the performance of individuals in the form of genomic estimated breeding value (GEBV), and finally to select for the elite individuals to be used in the breeding program [START_REF] Borém | Biotechnology and Plant Breeding -Applications and Approaches for Developing Improved Cultivars[END_REF].

In the past decade, GS was conducted in many species of animals [e.g. cattle [START_REF] Hayes | Genomic selection in dairy cattle: Progress and challenges[END_REF], chicken [START_REF] Wang | Application of genomic selection using an evenly spaced low-density marker panel in broiler chickens[END_REF], and pig [START_REF] Tribout | Efficiency of genomic selection in a purebred pig male line[END_REF]] and plants [e.g. maize [START_REF] Owens | A foundation for provitamin a biofortification of maize: genomewide association and genomic prediction models of carotenoid levels[END_REF], wheat [START_REF] Storlie | Genomic selection accuracy using historical data generated in a wheat breeding program[END_REF], apple [START_REF] Kumar | Genomic selection for fruit quality traits in apple (Malus×domestica Borkh[END_REF]]. With the availability of high-throughput sequencing technology, it is practicable for researchers and breeders to use information from dense genetic markers to benefit from genetic and breeding studies.

The effectiveness of many factors in GS have been tested [START_REF] Asoro | Accuracy and training population design for genomic selection on quantitative traits in elite North American oats[END_REF][START_REF] Würschum | Genomic selection in sugar beet breeding populations[END_REF], mostly aim to improve accuracy in prediction. Besides, attempt to use less markers in order to reduce genotyping cost was made [START_REF] Wang | Application of genomic selection using an evenly spaced low-density marker panel in broiler chickens[END_REF]. It has been found that prediction accuracy dropped when fewer markers were used in GS. However, increasing the number of markers was not always improving the prediction (i.e. accuracy reached a plateau when 3000 markers were fitted in the model) (Duangjit et al., under review). In addition, when minimizing markers number, it is possible that the number of individuals exceed the number of markers. This causes high mean-squared error (MSE) which can be fixed by performing shrinkage [START_REF] Stein | Inadmissibility of the usual estimator for the mean of a multivariate normal distribution[END_REF]. In the rrBLUP R package, shrinkage was implemented [START_REF] Duangjit | Ridge regression and other kernels for genomic selection with R package rrBLUP[END_REF]R Development Core Team, 2014). It has been previously shown that shrinkage estimation improved accuracy of GEBVs using rrBLUP [START_REF] Endelman | Shrinkage estimation of the realized relationship matrix[END_REF][START_REF] Zhao | Choice of shrinkage parameter and prediction of genomic breeding values in elite maize breeding populations[END_REF].

In this study, we want to test the effect of shrinkage of methionine and proline fruit contents from publicly available data of tomato. Here, we assessed shrinkage intensity that minimizes the expected MSE when different ranges of low marker density used in the rrBLUP model. We also evaluated the effect of shrinkage on the prediction accuracy.

MATERIALS AND METHODS

Statistical Model in Genomic Selection

Genotypic and phenotypic data used in this study is available publically, from a broad-based population of tomato accessions [START_REF] Sauvage | Genome-wide association in tomato reveals 44 candidate loci for fruit metabolic traits[END_REF]. Previous cross-validation study of genomic selection with different sizes of training set has revealed the potential of genomic selection using ridge-regression best linear unbiased prediction (rrBLUP) statistical model [START_REF] Asoro | Accuracy and training population design for genomic selection on quantitative traits in elite North American oats[END_REF]. The study showed that the high number of individuals in training step resulted in high accuracy of prediction. Therefore, from the population of 163 tomato accessions, 122 (75%) accessions were used to fit the model, and 41 (25%) accessions were used as a criterion in validation step in this study. The analyses were performed in rrBLUP package in R software published by [START_REF] Duangjit | Ridge regression and other kernels for genomic selection with R package rrBLUP[END_REF] (see also: https://cran.r-project.org/web/packages/rrBLUP/index.html).

Mixed model for prediction of breeding values were implemented with the model

Y = 1µ + Xg + e
where Y is vector of observed phenotypic value, µ is overall mean of the training set fitted as fixed effect, g is a vector of random SNP effect, X is an incidence matrix g, constructed from covariates based on the genotype, and e is residual effect. Genomic estimated breeding value (GEBV) was predicted using genotypic information, and SNP effects obtaining from mixed.solve function in rrBLUP [START_REF] Duangjit | Ridge regression and other kernels for genomic selection with R package rrBLUP[END_REF].

Shrinkage Estimation in rrBLUP

Marker matrix (X) was created by decoding bi-allelic loci to be X ∈ {-1, 0 ,1}. Shrinkage estimation was performed with A.mat function in the rrBLUP package. Estimations were repeated with different number of markers, which were randomly selected from a set of 5995 SNP markers [START_REF] Sim | Development of a large SNP genotyping array and generation of highdensity genetic maps in tomato[END_REF]. Shrinkage intensities when 250 markers were randomly picked and fitted into the rrBLUP model were estimated from the software. The averages of intensities which lead to minimal mean square errors were calculated from 1000 iterations. Calculations were made for different sets of markers (i.e. 500, 1000, and 1500).

Breeding Value Prediction

Population accuracy was predicted using 75% (122 accessions) of tomato population. The shrinkage intensity used in this analysis was ranged based on results from the first part (i.e. at 1.0, 2.0, 3.6, and 7.0%), and also at zero as a non-shrinked estimation. In order to assess effects of shrinkage in genomic selection, accuracies from shrinked and non-shrinked estimations were compared.

Finally, prediction accuracies were evaluated by correlating values between predicted breeding values (GEBVs) and measured phenotypic data of methionine and proline fruit contents as reported in [START_REF] Sauvage | Genome-wide association in tomato reveals 44 candidate loci for fruit metabolic traits[END_REF]. Average values and standard deviations were calculated from 1000 iterations.

Statistical significant difference between i) shrinked and non-shrinked methods and ii) shrinkage intensities were evaluated using t-tests.

RESULTS AND DISCUSSION

Estimated Optimal Shrinkage

Shrinkage intensity values under the criteria to minimize the expected MSE were obtained from this study. The optimal shrinkage intensity increased when smaller number of markers were randomly selected from a set of 5995 markers. The minimum (0.01±6.938x10 -18 ) was obtained from using 1500 markers, while the highest intensity was found when a set of random 250 markers was used (0.07±0.007) (Figure 1).

The results were estimated from random set of 250, 500, 1000, and 1500 out of a total set of 5995 markers. As the size of marker set is bigger, the shrinkage intensity is closer to zero. Difference in shrinkage intensity between 250 and 500 markers was significantly greater than that between 1000 and 1500 markers (P<0.05). A similar trend was also found in rice, maize, barley, and pig populations as studied by Endelman and Jannick (2012) where approximate 10% shrinkage was found, when a set of 96 markers was used.

However, very low number of markers (less than 250 markers) was not tested here as it was assumed to cause poor prediction ability.

Effects of Shrinkage on Prediction Accuracy

The accuracies from shrinked and non-shrinked approaches were compared in the two traits. When shrinkage was performed, in methionine fruit content, accuracy was 0.136±0.150 when 250 markers were included in the model. Accuracy increased to 0.143±0.143 and 0.147±0.148 when 500 and 1000 markers were used, respectively. Although, the accuracy slightly dropped when used 1500 markers, they were not significantly different from accuracy calculated from 1000 markers (Table 1). Similar trends were observed in proline fruit content; the larger the number of markers, the higher the accuracy of predicting breeding value.

Accuracy increased from 0.337±0.104 (used 250 markers) to 0.369±0.096 (used 1500 markers). This can be explained by the fact that markers with higher effect were fitted into the model.

When compared to the accuracies obtained from non-shrinked approach, for both traits, in most cases, accuracy values were higher when shrinkage was performed (Table 1 andFigure 2). When 250 markers were included in the model, accuracy was 0.129±0.148 without shrinkage. When shrinked with intensity of 7% (average shrinkage intensity when used 250 markers), accuracy increased to 0.136±0.150.

The difference was significant at P<0.05. This trend was not observed when more markers were added, and similar result was not found in proline fruit content. Although with a low number of markers used (m≤1500), proline fruit content with high heritability (h 2 =0.773) had higher accuracy than methionine fruit content (h 2 =0.427), as shown above. This result agreed with previous study of traits with different heritability [START_REF] Wimmer | Genome-wide prediction of traits with different genetic architechture through efficient variable selection[END_REF] supporting that trait with high heritability is the trait underlined with big proportion of genetic component. The results showed that significant increase of accuracy of GEBV, for most cases, cannot be obtained from shrinkage in this structured tomato population, particularly for the methionine and proline fruit content, which agreed with results from Endelman and Jannick (2012) where shrinkage can significantly increase GEBV only in unstructured population.

However, the significant accuracy gain was found when shrinked at 7% only in a low heritability trait (methionine). This revealed that, in trait with high heritability, shrinkage does not help improving accuracy, as reported by Endelman and Jannick (2012). Overall, as using methionine and proline fruit contents as case studies, factors such as numbers of markers and shrinkage affect genetic prediction using the rrBLUP method. Moreover, genetic background (i.e. heritability) of each trait also plays important role. This study showed that shrinkage benefits GS in trait with low heritability when the marker number is low. In tomato, the low-cost (due to small number of markers use)

and the most efficient number of markers need to be revealed.

Figure 1

 1 Figure 1 Optimal shrinkage intensity predicted by rrBLUP. Boxplot of shrinkage intensity estimated by using 122 accessions in training step with different sets of markers. Midbar and dot indicate average and median from 1000 imputations. M250, M500, M1000, and M1500 indicate number of markers used in statistical model training step.

Figure 2

 2 Figure 2 Impact of shrinkage on prediction accuracy. Boxplot of prediction accuracy estimated by rrBLUP model using 122 accessions in training step with different sets of markers. Midbar and dot indicate average and median from 1000 imputations. n and s represent non-shrinked and shrinked calculation; numbers (i.e. 250, 500, 1000, and 1500) indicate number of markers used in statistical model training step.

Table 1

 1 Prediction ability in methionine and proline traits obtained from genomic selection with rrBLUP model.

	Traits		Methionine Proline
	Heritability		0.427	0.773
		250	0.136±0.150* 0.337±0.104
	Shrinked	500	0.143±0.143 0.355±0.098
	(mean±SD)	1000	0.147±0.148 0.355±0.103
		1500	0.144±0.145 0.369±0.096
		250	0.129±0.148* 0.343±0.104
	Non-shrinked	500	0.134±0.149 0.354±0.098
	(mean±SD)	1000	0.147±0.144 0.357±0.103
		1500	0.141±0.145 0.358±0.096
	Mean and standard deviation (SD) are shown. Mean accuracies are the average correlation values
	of GEBVs and measured phenotypic values. Prediction was performed using 122 accessions in training step
	with different numbers of markers (1000 imputations). Heritability of each trait is from Sauvage et al. (2014).
	Significant difference assessed by t-test is indicated by asterisk (*).

ACKNOWLEDGEMENTS

This work was supported by the European Union (European Solanaceae grant no. PL016214-2). We would like to thank to Jeffery Endelman (University of Wisconsin-Madison, USA) for his advises on our work.


Organic farming as a factor for territorial development: a comparative perspective

In various European countries, organic farming acts as a driving factor for territorial development, forming initiatives like the Biovallée in France, Biodistretti in Italy or Bioregionen in Austria. These initiatives aspire to create 'model regions' for sustainable development not only in agriculture, but in a wider perspective. While the overall objective is similar for all approaches, the outcomes differ as our analysis of three European territories shows. 63

INTRODUCTION

There are numerous factors encouraging or hampering the success of rural development, like initiating actors, endowment with endogenous resources, public support, framework conditions and so forth (Bryden & Hart 2004). For long term sustainable rural development, the combination of all of these factors seems to be crucial. As a result, there is generally more than one possible development path, and, according to the concept of neo-endogenous development [START_REF] Ray | Culture, intellectual property and territorial rural development[END_REF], a conscious choice is necessary. Our comparison of three cases, which apply organic farming as a guiding principle for territorial development, analyses the impact of different governance structures and institutional settings on the territoriality of the development approach. The case study material includes interviews, institutional reports and available secondary scientific literature and statistical data.

THE CASE STUDY REGIONS

In the Mühlviertel (Upper Austria), endogenous rural development and organic farming dates back as far as to the early 1980s. However, the current "Bioregion Mühlviertel" was formed in 2010 by 7 LEADER regions and the Euregio 'Bayrischer Wald-Böhmerwald' in a broad participative process, resulting in a comprehensive regional development concept (www.bioregion-muehlviertel.at).

In France, the Biovallée is located in the Drôme valley, in the Rhône-Alpes region. Like the Mühlviertel, it is considered as a cradle of organic farming and has a long history of rural development. The Biovallée project was launched in 2009 by local authorities, building on public programs supporting organic farming, which had been set up already in the early 1990s. The current project embraces a wide range of objectives concerning energy, waste 63 Markus Schermer (markus.schermer@uibk.ac.at) The Biodistretto Cilento (www.biodistretto.net) is situated in the region of Campania in the south of Italy. It was created 2009 with the support of the organic farming association (AIAB) after a series of public events with local stakeholders and comprises all levels of local government. The official memorandum of understanding included pilot activities like organic group certification, specific production guidelines for organic producers, an awareness campaign and the establishment of various short supply chain marketing initiatives.

All three territorial projects want to position themselves as model regions for sustainable rural development. They aspire to turn from "the hinterland of the productivist period to the foreland of the quality period" (like a political slogan from the Drôme valley framed it in 1995). However, the three organizational set-ups as well as their historical evolution differ significantly.

RURAL DEVELOPMENT STRATEGIES AS BACKGROUND OF PRESENT ORGANIZATION STRUCTURES

The Austrian case builds on the tradition of the endogenous development approach from the late 1970s. Innovative projects were initiated with a focus on local human, cultural and natural resources. The successful initial results of this approach later formed the basis for an 'eco-social' agricultural (and rural) policy in the mid-1980s [START_REF] Schermer | From 'Food from Nowhere' to 'Food from Here': Changing Consumer-Producer Relations in Austria[END_REF]. Rural development, with the goal of supporting a small scale farm structure, remained a substantial part of the agricultural sectors' policy. This explains why the people who initiated the Bioregion (and who are still very influential) came from the mainstream side of agricultural administration. However, it appears that the configuration of the LEADER groups in the Mühlviertel, mirroring the different economic sectors, prevents the agricultural sector to take the lead. This makes it difficult for the Bioregion to be accepted as an overarching institution by the various sectors it wants to comprise (i.e. energy, tourism, education and handicraft) and to achieve a holistic territorial approach.

In France, the Biovallée project was created by the four districts of the valley. In the 2000s, the districts built together a first version of the Biovallée project in the frame of a national program focused on key value chains. With a program of the Rhône-Alpes Region aimed at fostering sustainable development on small territories, the Biovallée project then evolved into a much more integrated program for rural development, with organic farming as a key factor. Although the district authorities in charge of the project consulted agricultural actors in the appraisal process, they strived to keep a stronghold on the agricultural chapter of the project. This results in a current position that favours public utility rather than profitability, and employment-generating smallscale farming rather than industrial organic farming.

In Italy, Bio-distretti can be seen as a specific interpretation of the combined notions of 'rural districts' and 'quality agro-food districts', both defined by the Italian Agricultural Act. In contrast to 'industrial districts' which focus on clusters of small enterprises and the local municipalities, these concepts include the natural environment, civil society and the production of very specific goods or services [START_REF] Brunori | Differentiating countryside: Social representations and governance patterns in rural areas with high social density: The case of Chianti, Italy[END_REF]. The hybrid construction of this 'Bio-distretti' approach explains why a national organization like AIAB (Italian Association for Organic Agriculture) who deals with both, 'rural districts' as well as 'quality agro-food districts', is the main promotor and why it was possible to initiate already a number of new Bio-distretti following the model of the Cilento.

CONSEQUENCES

First of all, the organizational structure determines to some extent the measures applied in the territorial development strategy. In the case of Biovallée and Bio-distretto, the inclusion of administrative institutions (albeit on different levels) has resulted in a more integrated approach for rural development, embracing a larger scope, whereas in the Mühlviertel, the focus remained more agricultural.

Secondly, the involvement of different economic stakeholders finds its expression in the orientation of the supply chains. While in the Biovallée and in the Cilento, entire chains from production to consumption, including public catering etc. have been progressively built up, in the Mühlviertel, strong private organic processors (breweries, bakeries and butcheries) are the backbone of marketing activities so far.

Thirdly, the relationship between organic and conventional actors in the region is decisive for a further development of the territorial approach. On farm level, the territorial initiatives seem to stimulate conversion to organic farming. For instance, in the Biovallée, many conventional actors have converted totally or partially to organic farming, and most conventional and organic farmers have good relationships. For example, a farmers' cooperative marketing grain has set up a 100% organic farming goal, and half the trainings provided by the local agricultural school are dedicated to organic farming. Also in the Mühlviertel, the aim is to integrate partially converted organic processors and to stimulate conversion. The regional agricultural school is even the first organic school in Austria. In the Cilento, organic and conventional farmers jointly participate in training initiatives organized by the Bio-distretti which facilitates the convergence of farmers' interests and behaviours.

In turn, the relationships on the level of organizations may be different. While it seems to be less conflicting in the Austrian case, where the agricultural administration is the paramount actor, in the French case the Chamber of agriculture has long been in a conflictual relationship with the local authorities, denying their competence and legitimity to define an agricultural policy.

CONCLUSIONS

The orientation of endogenous development processes depends to a large extent on the configuration of actors in the organizational structure. As our results indicate, the present composition of actors mirrors the initial actors who were building on historical national and regional rural development policies. Therefore path dependencies determine to a large extent the configuration and ultimately the manifestation of territorial development through organic agriculture. This impacts the construction of supply chains as well as the social relations between conventional and organic farmers and their organisations.

ACKNOWLEDGEMENT

The authors acknowledge the financial support for this project provided by transnational funding bodies, being partners of the FP7 ERA-net CORE Organic II project HealthyGrowth.


Magdalena Kristiawan
email: magdalena.kristiawan@nantes.inra.fr

Guy G Della Valle

Kamal Kansou

Laurent Chaunier

Amadou Ndiaye

Bruno Vergnes

Chantal David

A phenomenological model of starchy materials expansion by extrusion

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

During extrusion of starchy products, the molten material is forced through a die so that the sudden pressure drop causes part of the water to vaporize, giving an expanded cellular structure. At die outlet, the material cools down, crosses glass transition T g and becomes solid. No simple model is available to describe satisfactory dynamic, multiphysic and multiphase phenomena during expansion. Current models are too complex to be coupled with simple mechanistic model of co-rotating twin-screw extrusion process, in order to predict the foam cellular structure. Our objective is to elaborate a phenomenological model of expansion, simple enough to be coupled with Ludovic ® , a simulation software of twin screw extrusion process. From experimental results that cover a wide range of thermomechanical conditions, a concept map of influence relationships between input and output variables is built. It takes into account the phenomena of bubbles nucleation, growth, coalescence, shrinkage and setting, in a viscoelastic medium. The input variables are the moisture content MC, melt temperature T p , specific mechanical energy SME, shear viscosity  at the die exit, computed by Ludovic ® , and the melt storage modulus E'(T p >T g ). The latter represents the elongational viscosity, and takes into account the influence of starch amylose content. The outputs of the model are the macrostructure (expansion indices and anisotropy factor), and cellular structure (fineness) of solid foams, determined by X-ray tomography. Then a general model is suggested:

VEI=(/ 0 )
n in which VEI is the volumetric expansion index. The model parameters, and n depend on T p , MC, SME and E'. The link between macroscopic anisotropy and fineness is also established, allowing the prediction of cellular structure. Finally, the model is validated using experimental data of wheat flour extrusion from literature.


M Kristiawan
email: magdalena.kristiawan@nantes.inra.fr

G Della Valle

A Ndiaye

B Vergnes

C David

Poster for "Biobased composites & blends for structural materials" A phenomenological model of starch expansion by extrusion

The expansion phenomenon is a key-point of the development of extruded starch based composites. During extrusion, the molten material is forced through a die so that the sudden pressure drop causes part of the water to vaporize, giving an expanded cellular structure. The knowledge of the cellular structure is important because it impacts the mechanical properties of the foams, its texture, etc 1 . The moisture is lost due to evaporation and heat transfer, as the material cools down. Thus, the material crosses glass transition T g and becomes solid. No simple deterministic model is available to describe satisfactory dynamic, multiphysic and multiphase phenomena during expansion. Current models 2,3,4 are too complex to be coupled with simple mechanistic model of co-rotating twin-screw extrusion process, in order to predict the cellular structure of starchy foams.

Our objective is to elaborate a phenomenological model of expansion, simple enough to be coupled with Ludovic ®5 , a simulation software of twin screw extrusion process. From experimental results that cover a wide range of thermomechanical conditions, a concept map of influence relationships between input and output variables is built. It takes into account the phenomena of bubbles nucleation, growth, coalescence, shrinkage and setting, in a viscoelastic medium. The input variables are the moisture content MC, melt temperature T p , specific mechanical energy SME, shear viscosity  at the die exit, computed by Ludovic®, and the melt storage modulus E'(T p >T g ). The latter represents the elongational viscosity, and takes into account the influence of formulation. The outputs of the model are the macrostructure (expansion indices and anisotropy factor), and cellular structure (fineness) of solid foams, determined by X-ray tomography. Then a general model is established (R 2 = 0.88): VEI=(/ 0 ) n in which VEI is the volumetric expansion index. The model parameters, and n depend on T p , MC, SME and E'. The link between macroscopic anisotropy and fineness is also established, allowing the prediction of cellular structure (R 2 = 0.84). Finally, the model is validated using experimental data of wheat flour extrusion, enriched with fibre, from literature, with R 2 = 0.77 for predicted VEI.

The integrative modelling approach of the extrusion process planned in this work will further provide users from academy and industry with the necessary tools to formulate and elaborate extruded starch based composites with potentially improved functional properties. The possibility of optimizing the process will include criteria such as minimizing energy with limited loss of product quality.


domain: sdv sde

text:
UMR7618«

  Institut d'Ecologie et des Sciences de l'Environnement-Paris» Comparison of artificial and natural selections, the case of nutrient acquisition in crop plants S. Barot, IRD, S. Boudsocq, N. Loeuille Artificial and natural selections are tightly connected  Based on the same fundamental mechanisms (genetic variability, transmission, selection)  Right from the start they have been associated by Darwin Organisms used by humans are the result of both natural So far there are very few models comparing explicitly the consequences of natural and artificial selections  A simple mathematical model to predict the evolution of plants capacity to take up mineral nutrients and its consequences  Comparison of the consequences of pure artificial or natural selections on production and nutrient losses Is there space for natural selection within artificial selection in agriculture? In traditional agricultures natural selection tends to be important because genetic diversity is maintained and locally managed  Artificial selection allows to improve through group selection collective properties of species, e.g. production, biomass  Idea that crop breeding has increased yield through group selection and a decrease in competitive ability at the individual scale (Denison 2003)  Natural selection of crops within fields could allow for a Boudsocq, S., S. Barot, and N. Loeuille. 2011. Evolution of nutrient acquisition ... Proc. Royal. Soc London B 278:449-457. The trade-off at the individual scale between nutrient uptake and nutrient losses seems to lead to a trade-off at the ecosystem scale between the yield and nutrient retention, i.e. short term vs. long term This gives arguments to integrate some natural selection within crop breeding  The model suggests that there is a kind of vicious circle: selecting in an intensive cropping context (high fertilizer inputs, high exportations of nutrients) increases the negative impact of artificial selection on nutrient losses (results not shown)


Maïmouna Coura Koné

Martine M Chebrout

H Jan

Renaud Fleurot

Niels Galjart

Pierre Adenot

Nathalie Beaujean

Marie Pascale

M P Debey

Amélie Bonnet-Garnier

Link between organization and transcription of Ribosomal RNA genes in mouse growing oocytes and at the very beginning of embryonic development

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

  Figure 1

*


Cedric Chaveroux

Alain Bruhat

Valerie Carraro

Julien Averous

Céline Jousse

Anne-Catherine Maurin

Yuki Muranishi

Laurent Parry

Jacques Mallet

Philippe Ravassard

Cedric Chaveroux

Valerie Carraro

Cédric Chaveroux

Valérie Carraro

Pierre Fafournoux

Development and optimization of a new gene regulation system controlled by nutrition applicable for gene therapy

GCN2 senses Essential Amino Acids (EAA) deficiency in the blood caused by the consumption of a diet lacking one EAA. Activation of this pathway leads to an increase in the translation of ATF4 transcription factor that functions as a master regulator for transcription of specific target genes playing a crucial role in nutrional stress adaptation.

INTRODUCTION

Our lab is specialized in nutrition research and mainly in characterizing the molecular mechanisms regulating the cellular adaptation to a nutritional stress. More specifically, eating a meal devoid of one Essential Amino Acid (EAA) causes a dramatic decrease of the limiting EAA in the blood, which in turn activates the GCN2/ eIF2α/ATF4 signaling pathway (Figure 1). This leads to a translational up-regulation of the transcription factor ATF4 that binds to a particular DNA sequence: the AARE (Amino Acid Response Element) to initiate a transcription program allowing the stress adaptation.

In gene therapy, the control of transgene expression remains a major concern. Therefore, we have generated an innovative gene regulation system controlled by nutrition by transfering the AARE in an artificial patented promoter. This system is associated to an EAA-deficient inducing diet developed in our lab. We are looking for collaborations and partners interested in developing and testing this AARE-Gene system for gene therapy applications in different pathological models.

Generation

Contact: pierre.fafournoux@clermont.inra.fr, alain.bruhat@clermont.inra.fr, cedric.chaveroux@clermont.inra.fr In vivo validation in progress

Figure 7 :

 7 Figure 7 : Induction of the AARE-controlled expression of TRAIL in response to an EAA starvation leads to apoptosis in glioblastoma cell line (A) Gli36-Luc cells were infected with lentiviral vectors containing the AARE-TRAIL sequence. (B) EAA induction of AARE-TRAIL system expression leads to apotosis. (C) Kinetic analysis of EAA induction of AARE-TRAIL system expression. (D) Viability assay of Gli36-Luc cells infected with lentiviral vectors containing AARE-TRAIL or AARE-GFP sequences in leucine-starved Gli36-Luc cells (16 h). (E) TRAIL release measurement (Elisa kit) in culture media, 16 h post leucine starvation. (F) Apotosis induction in parental cells caused by paracrine effect of TRAIL.

Figure 4 :Figure 2 :

 42 Figure 4 : Rapid change in the plasmatic amino acid concentration following the consumption of a complete and an EAA-deficient diet . (A) Mice were fed either with a control (Ctr) or a leucine-deficient diet (-leu) for 20 to 120 min (B) or refed for 2h on the control diet after a 2h-consumption of the leucine-deficient diet (-leu/+leu).

Figure 1 :

 1 Figure1: Presentation of the GCN2/eIF2α/ATF4 pathway controlling the AARE-Gene system activity. GCN2 senses Essential Amino Acids (EAA) deficiency in the blood caused by the consumption of a diet lacking one EAA. Activation of this pathway leads to an increase in the translation of ATF4 transcription factor that functions as a master regulator for transcription of specific target genes playing a crucial role in nutrional stress adaptation.

Figure 3 :

 3 Figure 3 : The AARE-Gene system can be activated by physiological EAA concentrations and requires GCN2 and ATF4 expression. (A) The plasmid construct contains two copies of the TRB3 AARE fused to the minimal promoter thymidine kinase (TK) and the Luciferase (LUC) coding sequence. This transgene is inducible (B) by different concentration leucine (C) via GCN2 (amino acid starvation) and the transcription factor ATF4.

CFigure 5 :Figure 6 :Figure 6 :

 566 Figure 5 : The reversible AARE-Gene system is induced the most in response to diets lacking Isoleucine, Valine or Threonine and can be used for transgene delivery in the liver, pancreas or the brain (A) Process for generation of the AARE-LUC mice strain. (B) Inducibility test of the AARE-Gene system in response to a diet devoid of one Essential Amino Acid (EAA) or one Non-Essential Amino Acid (NEAA) in the AARE-LUC transgenic mice. (C) Identification of tissues sensitive to EAA deficiency. (D) Demonstration of the reversibility of transgene expression following the consumption of a complete diet


Sandrine Costa-Migeon Costa

Sylvie Bureau

Selma Tozanli

Jean Marc

ILLIAD project: sustainable, local or localised, innovative food chains

come


est destinée au dépôt

Host plant specialization influences the spread of endosymbiotic parthenogenesis in seed wasps (Hymenoptera: Torymidae) Abstract: Wasps of the Megastigmus genus are highly specialized on seeds of gymnosperms (Pinaceae and Cupressaceae) or angiosperms (Rosaceae and Anacardiaceae), which strongly shaped their evolutionary history and influences many processes of their population dynamics. When several wasp species exploit the same host, they strictly require the same ecological niche, which is then particularly propitious to direct intra-or interspecific interactions.

In this study, we investigated how such host-mediated interactions can drive the epidemiology of thelytokous parthenogenesis within the Megastigmus genus. In Hymenopterans, thelytokous parthenogenesis is a form of spontaneous loss of sexuality leading to strong distortion of sex ratio towards females and resulting from mutation, hybridization or infection by bacterial endosymbionts. In the genus Megastigmus, the dominant and ancestral form of parthenogenesis is by far arrhenotoky (a form of sexuality) as thelytoky characterizes only a minority of species, but both arrhenotokous and thelytokous species can occur in sympatry on gymnosperm or on angiosperm hosts. In this context, we address specifically the potential for phylogeny, ecology and infection by parthenogenesis-inducing endosymbionts to drive the spread of thelytoky within this group of seed wasps.

We first performed a large literature survey to examine the distribution of thelytoky in these wasps across their respective obligate host plant families. Second, we tested for thelytoky caused by endosymbionts by screening in 15 arrhenotokous and 10 thelytokous species for Wolbachia, Cardinium, Arsenophonus and Rickettsia endosymbionts and by performing antibiotic treatments. Finally, we performed phylogenetic reconstructions to examine the evolution of thelytoky in Megastigmus and its possible connections to both endosymbiont infection and host plant specialization.

We demonstrate that thelytoky evolved from ancestral arrhenotoky through the horizontal transmission and the fixation of the parthenogenesis-inducing Wolbachia. We find that ecological specialization in Wolbachia's hosts was probably a critical driving force for Wolbachia infection and spread of thelytoky, but also a constraint. Sharing a narrow ecological niche opens an encounter filter between species, but also restricts the host spectrum to the few species exploiting a particular resource. Niche overlap opportunity being closely related to phylogenetic proximity between species, a compatibility filter can be open and facilitates symbiont infection. Our work shows that community structure of insects is a major driver of the epidemiology of endosymbionts and that competitive interaction among closely related species may facilitate their horizontal transmission.

Keywords:

Ecological specialization, epidemiology, parthenogenesis, Megastigmus, phylogeny, thelytoky, Wolbachia

  Thomas Boivin, Hélène Henri, Fabrice Favre, Cindy Gidoin, Philippe Veber, Jean-Noël Candau, Alain Roques, Marie-Anne Auger-RozenbergTo cite this version:Thomas Boivin, Hélène Henri, Fabrice Favre, Cindy Gidoin, Philippe Veber, et al.. Host plant specialization influences the spread of endosymbiotic parthenogenesis in seed wasps (Hymenoptera: Torymidae). IUFRO joint meeting: 7.03.06 "Integrated Management of Forest Defoliating Insects" and 7.03.01 "Cone and seed insects", 2014, Antalya, Turkey. hal-02740030

Thomas Boivin 1 , H. Henri 2 , F.Vavre 2 , Gidoin C. 1 , Veber P. 2 , Jean Noel Candau 1,3 , Alain Roques 4 , Marie-Anne Auger-Rozenberg 4

  National Resources Canada, Canadian Forest Service, Great Lakes Forestry Ctr, Sault Ste Marie, ON P6A 2E5, Canada 4 INRA, UR633 Unité de Recherche de Zoologie Forestière, 45075 Orléans, France

	1 INRA, UR629 Ecologie des Forêts Méditerranéennes, URFM, F-84914 Avignon, France 2 Université de Lyon, F-69000, Lyon; Université Lyon 1 ; CNRS, UMR5558, Laboratoire de Biométrie et Biologie
	Evolutive, F-69622, Villeurbanne, France.

3


Christophe Richard

Valerie Gelin

Alexandre Neveux

Isabelle Hue

Yvan Heyman

Pascale Chavatte-Palmer

Embryo collection in clone cattle offspring

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M Robles

Chavatte-Palmer P

PERICONCEPTIONAL BODY CONDITION INDUCES PLACENTAL ADAPTATIONS BUT DOES NOT AFFECT FOAL GROWTH AND METABOLISM IN HORSES

Keywords:

Objectives: It has been shown in several species that the periconceptional environment can affect offspring long-term phenotype. This study aims to investigate the effects of periconceptional body condition on feto-placental biometry, post-natal foal growth and glucose metabolism.

Materials and methods: 32 saddlebred mares of similar size were allocated to one of two groups depending on their body condition score (BCS, 1-5 French scale) at the time of artificial insemination (AI). Group High (H, n=18) had a median BCS of 3.9 (range: 3-4.25) whereas group Low (L, n=14) had a significantly lower BCS (median: 2.5, range: 2-3.75, p=0.01). Both groups were kept in pasture until the 7 th month of gestation when they were housed indoors and fed forage and concentrate (barley). Food intake was not different between groups. Mares were weighed every 2 weeks and their BCS was monitored monthly. Placentas and foals were weighed and measured at birth. Foals were measured and their fasting glucose assessed regularly until 12 months of age. A frequently sampled intravenous glucose tolerance test (FSIGT) was performed at 3 days and 4 months of age. Results were analyzed using a Mann-Whitney test.

Results: H mares maintained a significantly higher BCS (median ≥3.75) than L mares from AI until foaling (median at foaling: 3.75, p<0.0001). L mares reached a peak BCS of 3.75 at the 7 th and 8 th month and thereafter lost BCS until foaling (median BCS at foaling: 2.75). Mares' body weight was not different between groups at any time. Gestation length did not differ between groups. H placentas tended to be 15% lighter with a 10% reduced surface compared to L placentas (p=0.071). Foals' weight and measurements at birth were not different but the placental efficiency (foal/placental weight) tended to be 12% higher in H mares (p=0.078). There was no difference in foals' growth until 12 months. H foals' fasting glucose tended to be higher at 3 days (p=0.063) but there was no difference in the glucose response to the FSIGT. Plasma insulin concentrations are pending.

Conclusion: H mares tended to have a lighter placenta and with a reduced surface area that was more efficient than L mares. Their foals tended to have greater fasting plasma glucose than L foals at 3 days. The fact that the BCS of H and L mares throughout gestation matched their BCS at AI highlight the importance of periconceptional BCS. This study follows a previous one showing that feeding mares in the 2 nd part of gestation with two different energy sources does not affect fetoplacental biometry and foal development until the age of 6 months (Peugnet et al 2015). Nevertheless, periconceptional BCS appears to induce placental adaptations that are currently being characterized.

This study was funded by the Institut du Cheval et de l'Equitation and by the Fonds Eperon (FOETALIM grant).


Hervé Garreau
email: herve.garreau@toulouse.inra.fr

Julien Ruesche

Hélène Gilbert

Elodie Balmisse

Florence Benitez

François Richard

Ingrid David

Laurence Drouilhet

Olivier Zemb

Microrabits : a factorial design to evaluate genetic and maternal effects on growth and feed efficiency in a line selected for residual feed intake

Keywords: feed efficiency, residual feed intake, growth, genetics

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Performances of growing rabbits are determined by their genotype and their environment. The effect of maternal environment is particularly important in this species. Improvement of feed efficiency is essential to increase the competitiveness of the rabbit industry but also to reduce the animal excretion, and consequently decrease the environmental impact of the production. It can be achieved in rabbit by selection on residual feed intake (RFI) or on growth under restricted feeding [START_REF] Drouilhet | Genetic parameters for two selection criteria for feed efficiency in rabbits[END_REF][START_REF] Drouilhet | Direct and correlated responses to selection in two lines of rabbits selected for feed efficiency under ad libitum and restricted feeding: I. Production traits and gut microbiota characteristics[END_REF]. However these selection strategies do not take into account the contribution of gut microbiota to improved feed efficiency, although some previous results have demonstrated its relation with digestive efficiency in chicken [START_REF] Narcy | Impact of Selection for Digestive Efficiency on Microbiota Composition in the Chicken[END_REF]. To further investigate the effects of the animal genotype and maternal environment on feed efficiency, an experiment based on cross fostering between a line selected on RFI and a non-selected control line was performed. Ultimately, it should allow disentangling the effect of animal genetic and dam microbiota transmission on the traits. The objective of this preliminary study was to estimate both host genotype effect and maternal environment effect on growth and feed efficiency in rabbit.

MATERIALS AND METHODS

Animal management

The experimental rabbit populations were issued from the INRA 1001 line [START_REF] Larzul | Selection for residual feed consumption in the rabbit[END_REF] and bred in the experimental INRA farm Pôle d'Expérimentation Cunicole Toulousain (Castanet-Tolosan, France), in accordance with the national regulations for human care and use of animals in agriculture. Two lines were used in this study: the G10 line, selected for 10 generations on RFI and the G0 line produced from frozen embryos of the ancestor population of the selected line. The 490 G10 and 410 G0 rabbits were produced in 3 batches with a 42 days interval.Within 48 hours following birth, every kit was fostered. In each batch, half of kits was fostered by G0 does and the second half of kits was fostered by G10 does. Does adopted alternatively kits from one line and from the other line in successive batches. Litters of 5 to 7 kits were made up, mixing sires families of kits within fostered litters. At weaning (32 days), each batch, 152 kits were placed in individual cages, 48 in digestibilty cages and the rest in collective cages of 4 to 5 animals. All animals were fed ad libitum the same commercial pelleted diet until the end of the fattening period (63 days).

Traits

Animals were weighed at weaning (BW32) and at 63 days of age (BW63). Individual feed intake (FI) was recorded in individual and digestibility cages and estimated in collective cages by dividing total feed consumption by the number of animals in the cage, taking into account death of animals when occuring prior to the end of the test. Average daily gain (ADG) was obtained by dividing the body weight gain during the test by the number of days of the growing period. Feed conversion ratio (FCR) was calculated as total feed intake divided by the body weight gain.

Statistical analyses

The RFI was computed as the residual of the multiple linear regression of total feed intake on average metabolic body weight (average body weight between weaning and end of the test to the power 0.75) to account for maintenance requirements and ADG to account for production requirements (REG procedure; SAS software). Fixed effects to be accounted for in the statistical analyses were tested using a linear model (GLM procedure, SAS, 2008): y ijklm = µ + kit line i + doe line j +batch k + housing l + batch k × housing l + e ijkml , (1) with y ijklm the trait value for animal k, kit line i the line of the animal (2 levels), doe line j the line of the foster doe (2 levels), batch k the batch of the animal (3 levels), housing l, the type of cage in which the animal was raised (3 levels). The only significant interaction between all fixed effects was batch k × housing l (P < 0.05), therefore no other interaction was retained in the models.

RESULTS AND DISCUSSION

Levels of significance of fixed effects are presented in Table 1. The batch effect and the batch × housing interaction, being significant for all traits, are not mentioned in this table. The kit line effect and the type of housing effect were significant for all traits (P < 0.001). The foster doe effect was significant only for FCR, G10 foster does showing an unfavorable effect (-0.06 ± 0.02 ). Least square means of the kit line and of the type of housing effects are presented in Table 2. The G10 animals were lighter than G0 rabbits at 32 days (-82.9 g) and at 63 days (-161 g). They also had a lower ADG (-2.36 g/day), FCR (-0.36), RFI (-548 g) and a lower FI (-839 g), illustrating a better feed efficiency. These results demonstrate that selection on RFI was efficient, as already reported [START_REF] Drouilhet | Genetic parameters for two selection criteria for feed efficiency in rabbits[END_REF][START_REF] Drouilhet | Direct and correlated responses to selection in two lines of rabbits selected for feed efficiency under ad libitum and restricted feeding: I. Production traits and gut microbiota characteristics[END_REF]. [START_REF] Nguyen | Response in residual feed intake in lines of Large White pigs selected for growth rate on restricted feeding (measured on ad libitum individual feeding)[END_REF] have also reported a successful selection experiment on RFI in pig. Concerning the type of housing, performances of rabbits raised in individual cages were similar to those raised in digestibility cages. However rabbits raised in collective cages were lighter at 63 days (-162 g approx.) and presented a lower ADG (-4.21 g/day approx.) than rabbits raised individually. They had also higher FCR, RFI and FI (around +0.45,+464 g et +205 g,respectively). [START_REF] Coulmin | Incidence du nombre de lapins par cage d'engraissement sur les performances zootechniques. 3 émes Journées de la Recherche Cunicole[END_REF] obtained similar results by decreasing the number of rabbit per cage: heavier animals with a higher ADG associated to smaller number of animals per cage, probably due to decreased loss of energy in relation with activity, but they reported no modification of FCR.

Kit and foster doe lines effects are shown in Figure 1. Compared to G0, G10 foster does had an unfavorable effect on FCR, irrespective of the kit line (-0.06). The maternal effect included the permanent environmental effect offered by the doe to the kits, its own genetic effect and its microbiota transmitted to kits. Our results reflect a negative maternal effect of the selected line G10 on feed efficiency. At this stage of the study, it is not possible to identify which component of maternal effect (milk, maternal behavior, microbiota...) was degraded by the selection [START_REF] Combes | Lapereaux de la naissance au sevrage : quels outils pour des lapereaux plus robustes ? 15 èmes Journées de le Recherche Cunicole[END_REF]. This can be related to negative correlations previously estimated in some studies between direct and maternal effects on production traits in rabbits [START_REF] David | The direct-maternal genetic correlation has little impact on genetic evaluations[END_REF]. In conclusion, FCR was strongly influenced by the genotype of the kit (Δ = 0.36, P < 0.001) and to a lesser extent by the maternal environment (Δ = 0.06, P < 0.05).

CONCLUSIONS

Our results demonstrate that selection on feed efficiency was successful. However maternal effects were degraded by the selection. Further investigations are undergoing to better understand the effect of selection on direct and maternal effects. These investigations include host genotyping and microbiota sequencing.

Figure 1 :

 1 Figure 1: Kit line and foster doe line effects on feed conversion ratio. *: P < 0.05 ; ***: P < 0.001.

Table 1 :

 1 Level of significance of fixed effects

	P

ns = non significant ; *: P < 0.05 ; **: P < 0.01; ***: P < 0.001.

Table 2 :

 2 Least square means for kit line and type of housing

		Kit line		Type of housing
	Trait	G0	G10	collective	digestibility	individual
	BW32 (g)	916 ± 6	833 ± 6
	BW63 (g)	2,624 ± 13	2,463 ± 12	2,436 ± 14 a	2,596 ± 20 b	2,599 ± 11 b
	ADG (g/day) 51.76 ± 0.28 49.40 ± 0.26	47.77 ± 0.32 a 52.08 ± 0.46 b 51.88 ± 0.25 b
	FCR	3.02 ± 0.02	2.66 ± 0.02	3.14 ± 0.02 a	2.69 ± 0.03 b	2.69 ± 0.01 b
	RFI (g)	298 ± 18	-250 ± 17	333 ± 20 a	-117 ± 29 b	-144 ± 16 b
	FI (g)	5,127 ± 23	4,288 ± 21	4,850 ± 26	4,645 ± 38	4,628 ± 21

a, b means with different letters are significantly different (P < 0.05).

ACKNOWLEDGEMENTS

Authors acknowledge all the staff of the INRA Pectoul experimental unit.