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This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of “omics” data and crop growth models. Part Five is dedicated to lessons learned from cases studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction. Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches.

So far, most potential applications of genomic prediction in plant improvement have been explored using cross validation approaches. This is the first empirical study to evaluate the accuracy of genomic prediction of the performances of progenies in a typical rice breeding program. Using a cross validation approach, we first analyzed the effects of marker selection and statistical methods on the accuracy of prediction of three different heritability traits in a reference population (RP) of 284 inbred accessions. Next, we investigated the size and the degree of relatedness with the progeny population (PP) of sub-sets of the RP that maximize the accuracy of prediction of phenotype across generations, i.e., for 97 F5–F7 lines derived from biparental crosses between 31 accessions of the RP. The extent of linkage disequilibrium was high (r2 = 0.2 at 0.80 Mb in RP and at 1.1 Mb in PP). Consequently, average marker density above one per 22 kb did not improve the accuracy of predictions in the RP. The accuracy of progeny prediction varied greatly depending on the composition of the training set, the trait, LD and minor allele frequency. The highest accuracy achieved for each trait exceeded 0.50 and was only slightly below the accuracy achieved by cross validation in the RP. Our results thus show that relatively high accuracy (0.41–0.54) can be achieved using only a rather small share of the RP, most related to the PP, as the training set. The practical implications of these results for rice breeding programs are discussed.

International audience; Salinity tolerance is an important quality for European rice grown in river deltas. We evaluated the salinity tolerance of a panel of 235 temperate japonica rice accessions genotyped with 30,000 SNP markers. The panel was exposed to mild salt stress (50 mM NaCI; conductivity of 6 dS m(-1)) at the seedling stage. Eight different root and shoot growth parameters were measured for both the control and stressed treatments. The Na+ and K+ mass fractions of the stressed plants were measured using atomic absorption spectroscopy. The salt treatment affected plant growth, particularly the shoot parameters. The panel showed a wide range of Na+/K+ ratio and the temperate accessions were distributed over an increasing axis, from the most resistant to the most susceptible checks. We conducted a genome-wide association study on indices of stress response and ion mass fractions in the leaves using a classical mixed model controlling structure and kinship. A total of 27 QTLs validated by sub sampling were identified. For indices of stress responses, we also used another model that focused on marker x treatment interactions and detected 50 QTLs, three of which were also identified using the classical method. We compared the positions of the significant QTLs to those of approximately 300 genes that play a role in rice salt tolerance. The positions of several QTLs were close to those of genes involved in calcium signaling and metabolism, while other QTLs were close to those of kinases. These results reveal the salinity tolerance of accessions with a temperate japonica background. Although the detected QTLs must be confirmed by other approaches, the number of associations linked to candidate genes involved in calcium-mediated ion homeostasis highlights pathways to explore in priority to understand the salinity tolerance of temperate rice.

The increase in rice production needed to meet future demand requires renewed cropping systems and rice varieties with enhanced resources use efficiency and adaptation to environmental stresses in the context of climate change. Genomic selection (GS) has the potential to accelerate the development of such varieties. We present an overview of the proof-of-concept studies conducted during the last decade with the aim of providing rice breeders with tailored GS methods and tools. These studies involved complementary breeding programs (pedigree breeding, population improvement, etc.), mobilising different compartments of rice genetic diversity (indica, tropical and temperate japonica), and targeting a wide range of traits (yield potential, nitrogen use efficiency, adaptation to alternate watering and drying, salinity tolerance, drought tolerance, exclusion of heavy metals, outcrossing and hybrid seed production abilities, etc.). The objective was to evaluate the importance of different factors known to influence the accuracy of genomic prediction: marker density, linkage disequilibrium, trait heritability and genetic architecture, characteristics of the training population, relatedness between training and candidate populations, statistical models, etc.). Our results showed notably that GS can accelerate genetic gain in both pedigree and population breeding schemes by increasing selection intensity and by shortening the selection cycle. Rice diversity panels provide accurate genomic predictions for complex traits in the progenies of biparental crosses involving members of the panel. Genomic prediction accounting for genotype-by-environment interactions offers an effective framework for breeding simultaneously for adaptation to an abiotic stress and for performance under normal cropping conditions. The degree of relatedness between the training and the candidate population matter more than the size of the training set per se. Whatever the genetic background of the training and the candidate populations (and the associated linkage disequilibrium), average marker density of more than one SNP every 20 kb does not improve prediction accuracy. Further simulation studies are needed to assess the impact of GS on long-term genetic gain and diversity, to adjust the GS strategy accordingly. In the light of these results, we propose a strategy for embedding international rice gene discovery and ecophysiological ideotype modeling research in a GS based rice breeding program.

Effective harnessing by crop breeding programs of genetic gains expected from the integration of genomic resources, high throughput phenotyping capabilities, and efficient statistical methods to model the complexity of empirical data requires adjustments of the breeding strategies. Tools that simulate breeding features are needed to explore the effects of those adjustments and their potential interactions. Simulations are useful because they allow rapid replicated testing of a wide range of hypotheses at low cost, for example, the initial feasibility of genomic selection or the impact of the reference population structure. Simulation of breeding strategies is well adapted to investigate long-term effects of selection, which are often infeasible using real experiments due to time and cost requirements. Different tools have been proposed to reflect the complexity of the studied population (genomes structure, genetic architecture of the traits, and relatedness among individuals). However, few of them are specifically designed to simulate breeding strategies in crop species. We have therefore developed breedgenr, a simulation tool dedicated to meet breeder's needs to rationalize the different steps of a breeding scheme. breedgenr is an R package that present two distinctive features compared to existing tools. First, breedgenr uses real genotypic and phenotypic data from breeding programs to generate the reference population. Thus, it limits the number of possible hypotheses and scenarios regarding the evolutionary history and the structure of the breeding populations. Second breedgenr is based on non-parametric approaches to calibrate genotype-phenotype relationship. Consequently, it does not rest on specific assumptions regarding the genetic model and the genetic architecture of the phenotypic traits considered. Robustness and functionality of breedgenr were evaluated using real datasets on rice and different breeding schemes. The objective was to design breeding schemes that integrate different genomic selection scenarios. The results confirmed the robustness of the calibration of genotype-phenotype relationships based on the chosen non-parametric kernel methods, and the capability of breedgenr to simulate breeding populations and different breeding schemes: pedigree breeding and recurrent selection. Further ascertaining of breedgenr robustness and adjustment-expansion of its functionalities are presented.

Background Plant root systems play a major role in anchoring and in water and nutrient uptake from the soil. The root cone angle is an important parameter of the root system architecture because, combined with root depth, it helps to determine the volume of soil explored by the plant. Two genes, DRO1 and SOR1, and several QTLs for root cone angle have been discovered in the last 5 years. Results To find other QTLs linked to root cone angle, a genome-wide association mapping study was conducted on two panels of 162 indica and 169 japonica rice accessions genotyped with two sets of SNP markers (genotyping-by-sequencing set with approximately 16,000 markers and high-density-rice-array set with approximately 300,000 markers). The root cone angle of all accessions was measured using a screen protractor on images taken after 1 month of plant growth in the Rhizoscope phenotyping system. The distribution of the root cone angle in the indica panel was Gaussian, but several accessions of the japonica panel (all the bulus from Indonesia and three temperate japonicas from Nepal or India) appeared as outliers with a very wide root cone angle. The data were submitted to association mapping using a mixed model with control of structure and kinship. A total of 15 QTLs for the indica panel and 40 QTLs for the japonica panel were detected. Genes underlying these QTLs (+/−50 kb from the significant markers) were analyzed. We focused our analysis on auxin-related genes, kinases, and genes involved in root developmental processes and identified 8 particularly interesting genes. Conclusions The present study identifies new sources of wide root cone angle in rice, proposes ways to bypass some drawbacks of association mapping to further understand the genetics of the trait and identifies candidate genes deserving further investigation. Electronic supplementary material The online version of this article (10.1186/s12284-017-0184-z) contains supplementary material, which is available to authorized users.

Rice cultivated gene pool includes two species. Asian rice, Oryza sativa, displays a very large phenotypic diversity resulting from a long history of domestication driven by human demographic expansion and sympatry with its wild relatives. African rice, Oryza glaberrima, represents a typical case of domestication bottleneck. Recent sympatry of the two species in Africa has given birth to new diversity. Current rice in situ genetic diversity results from the succession of a number of long-standing evolutionary events and the contemporary reversal of the trend of increasing diversity, referred to as genetic erosion. Since the early twentieth century, human demographic growth, agricultural modernisation and the advent of formal breeding systems, have affected the in situ diversity of cultivated rice species and their wild relatives. The evolutionary processes had produced a very large number of Landraces (LV) of which some 500,000 are conserved ex situ. The contemporary changes have resulted in the replacement of a large proportion of LV by a small number of Modern varieties (MV) in more than 70 % of rice-growing areas in Asia and Latin America, 38 % in Africa. The most important feature of rice in situ diversity emerging from our case studies in China, South and Southeast Asian countries, West Africa and Madagascar, is the diversity of situations. Aggregated data suggest massive absolute genetic erosion and sharp reduction of diversity indexes, particularly in irrigated ecosystems. Detailed surveys indicate smoother genetic erosion in rainfed ecosystems. However, the perspectives of rice in situ genetic diversity are gloomy even in rainfed ecosystems. The most realistic and promising option for the future is a dynamic management in the framework of the emerging concept of ecological intensification.

Recently, the conjunction of high-throughput marker technologies and new statistical methods has given birth to a new breeding strategy called genomic selection(GS).It refers to methods that use genome-wide dense marker genotyping for the prediction of genetic values with enough accuracy to allow selection based on that prediction alone. It consists of two steps: estimation of SNP effects within a training population (TP), and prediction of genomic estimated breeding values (GEBV) in the candidate population(CP)based on SNP genotypes. We present here GS for water use efficiency in rice, in the framework of a pedigree breeding scheme. The TP was composed of 284 accessions belonging to the temperate japonica and tropical japonica rice groups. The CP was composed of 99 F5-F7 lines derived from 36crosses involving 32 accessions of TP. The two populations were genotyped with an average marker density of 4.8perkb, with minimum minor allele frequency of 2.5.Phenotypic traits considered included flowering time (FL), grain yield (GY) and nitrogen balance index (NI)under conventional irrigation (CI) and aerobicsystem (AS).Phenotypes were modeled using two statistical regression methods: genomic best linear unbiased prediction (GBLUP) and reproducing kernel Hilbert Space (RKHS).The models were tested with three incidence matrixes corresponding to densities of 4.8, 9.5 and 13.8marker per kb, and to linkage disequilibrium (LD)thresholds of r²≤1, r²

Coping with heat stress involves different options that account for the ability of plants to escape (early anthesis time), avoid (panicle cooling through transpiration) or tolerate (presence of genes of interest) heat at flowering. First, variability in the time of day of anthesis was correlated with the mean of climatic variables calculated for the 7-day period before flowering, over four distinct seasons and four contrasted varieties. The best predictive variables (negative correlations) were Tmin and VPD, with high values of both being associated with early times. Second, depending on conditions, panicle temperature varied between 9°C below and 2°C above air temperature at 2 m. A significant positive correlation was obtained between spikelet sterility rate and maximum panicle temperature at flowering, whereas no correlation was obtained with air temperature. By extrapolation, this correlation predicted minimal sterility with a panicle temperature of 30 °C, and 50 % sterility with a panicle temperature of 33-34 °C. Third, a genome-wide association study of the sterility rate of 167 traditional and modern varieties (grown for six consecutive days at 37°C between 8 am and 2 pm at anthesis) detected 91 significant associations grouped into 12 independent regions located on eight chromosomes. The highest heat tolerance was detected for N22, an aus variety from India, and Peh Kuh, a traditional indica variety from Taiwan. Avoidance and tolerance appear as main genetic improvement pathways, whereas sensitivity of time of day of anthesis to air temperature and humidity seems already effective within the rice crop. (Texte intégral)

Roots are key organs for plants as transporters of water and nutrients. However, they are complicated to observe. To develop rice varieties with root systems adapted to the target environments (e.g. with a high number of deep, thick and highly branched roots for the upland ecosystem) without direct observation, a better knowledge of the genes involved is necessary. So far, only three genes influencing root architecture or nutrient uptake have been cloned in rice. Whole genome association mapping (WGAM) offers a fast access to new quantitative trait loci (QTLs) with a better resolution than conventional QTL mapping. Results on several panels are presently available. However, WGAM relies on statistics and its results need further validation using evidences from other approaches, notably functional genomics. The effects of genes with function on root development validated in Arabidopsis are being studied in rice (e.g. SHR and SCR or the family of leucine-rich repeat receptor-like kinases in our lab). We will present a summary of all these results.

Thanks to genome-scale diversity data, present-day studies can provide a detailed view of how natural and cultivated species adapt to their environment and particularly to environmental gradients. However, due to their sensitivity, up-to-date studies might be more sensitive to undocumented demographic effects such as the pattern of migration and the reproduction regime. In this study, we provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection. We simulated 100 populations along a selective gradient and explored different migration models, sampling schemes and rates of self-fertilization. We investigated the power and robustness of eight methods to detect loci potentially under selection: three designed to detect genotype-environment correlations and five designed to detect adaptive differentiation (based on F(ST) or similar measures). We show that genotype-environment correlation methods have substantially more power to detect selection than differentiation-based methods but that they generally suffer from high rates of false positives. This effect is exacerbated whenever allele frequencies are correlated, either between populations or within populations. Our results suggest that, when the underlying genetic structure of the data is unknown, a number of robust methods are preferable. Moreover, in the simulated scenario we used, sampling many populations led to better results than sampling many individuals per population. Finally, care should be taken when using methods to identify genotype-environment correlations without correcting for allele frequency autocorrelation because of the risk of spurious signals due to allele frequency correlations between populations. (Texte intégral)

Ouvrage en libre accès, document disponible en ligne : http://www.afd.fr/webdav/site/afd/shared/PUBLICATIONS/RECHERCHE/Scientifiques/A-savoir/06-VA-A-Savoir.pdf; International audience; The rise in world agricultural prices in 2008 revealed the fragility of food security in many developing countries. Poor populations in sub-Saharan Africa are the biggest victims of this fragility. Rainfed food crops can play a unique role on the continent by supplying regional markets, increasing farmers' incomes, and creating jobs in rural areas. Working within the framework of the regional dynamics launched in West and Central Africa, AFD, CIRAD and IFAD initiated three studies to (i) map the food crop production and consumption areas in the zone, (ii) identify the contributions of research on these supply chains, and (iii) analyze food crop project practices. This book summarizes this research, accomplished with African research and regional expertise centers (AGRHYMET, WECARD). It reports on current knowledge of the main food crop supply chains in the region: rice, corn, cassava, millet-sorghum, yam, groundnut and cowpea. Other areas remain to be explored to strengthen existing dynamics: how can intermediation professions be supported? How can a regional approach to these supply chains be developed so as to disseminate best practices, expand markets and foster synergy? What role in supporting these supply chains could be (re)assigned to research? How can the financing constraint, which is present throughout the supply chain, be overcome? This book aims to provide keys to decipher supply chain operations and the challenges facing food crop supply chains in this region.

A collection of accessions of Burkina Faso rice germplasm was evaluated for resistance using four Rice yellow mottle virus (RYMV) isolates: Ng122, Ng144, B27 and BF1. B27, an isolate from Benin was used first, followed by Ng122 and Ng144 (isolates from Niger), and BF1 an aggressive isolate from Burkina Faso was used last to assess the accessions status against RYMV. Fourteen-day-old plantlets were inoculated and symptoms scored fortnightly from 14 to 56 days post inoculation (dpi). Plant height of all accessions was recorded at 49 dpi with isolates Ng122 and Ng144. The Oryza sativa accessions of the collection were highly susceptible except one (BM24), which combined partial resistance and tolerance. Twenty one O. glaberrima accessions out of 48 were found resistant to Ng122 and Ng144. When these 21 accessions were subsequently screened with the aggressive RYMV strain BF1, eight of them displayed a delay in the appearance of RYMV symptoms while two showed resistance. The new sources of resistance identified in this study, could be exploited in breeding to control the spread of RYMV in Africa.

Présentation de l'éditeur : Rice is a strategic and political crop in many African countries. The hikes in rice prices since 2007 have shown the vulnerability of many African countries that depend on the world market for rice imports and the need to boost Africa's domestic production. The purpose of this book is to provide a comprehensive overview of Africa's rice sector and ongoing rice research and development activities, and indicate priorities for action on how to realize Africa's Rice Promise', i.e. the notion that Africa has sufficient land and water resources to produce enough rice to feed its own population and, in the long term, generate export revenues. The critical challenge facing the African rice sector is to enhance performance in production, processing and marketing to respond to a major concern that needs to be turned into an opportunity: the growing demand for rice as a preferred staple. This book discusses challenges and opportunities related to: sustainably increasing rice production and rice productivity; enhancing rice quality and marketing; promoting conducive policies for smallholder and agribusiness development; and strengthening impact-oriented rice research, extension and knowledge management. The analyses and case studies presented in this book will be a valuable resource for researchers, development agents from public and private sectors, rice value- chain actors and policy makers concerned with Realizing Africa's Rice Promise. Main contents. Foreword. Acknowledgements. Introduction. Section 1. Rice in Africa: an overview. 1. From Warda to AfricaRice: an overview of rice research for development activities conducted in partnership in Africa. 2. Africa's rice economy before and after the 2008 rice crisis. 3. Estimation of cultivated area, number of farming households and yield for major rice-growing environments in Africa. 4. Farmer perceptions of the biophysical constraints to rice production in Sub-Saharan Africa, and potential impact of research. Section 2. Rice genetic diversity and improvement. 5. A continent-wide, product-oriented approach to rice breeding in Africa. 6. Rice varietal release systems in Africa. 7. Diversity of rice and related wild species in Africa. 8. Gene flow in African rice farmers' fields. 9. Making rice genomics work for Africa. 10. Unlocking the Oryza glaberrima treasure for rice breeding in Africa. 11. Rice genetic improvement for abiotic stress tolerance in Africa. 12. Integration of molecular markers in rice improvement: a case study on resistance to rice yellow mottle virus. 13. Hybrid rice in Africa: challenges and prospects. 14. Development of an integrated rice seed sector in Sub-Saharan Africa: meeting the needs of farmers. Section 3. Sustainable productivity enhancement. 15. Towards a better understanding of biophysical determinants of yield gaps and the potential for expansion of the rice area in Africa. 16. Managing weeds of rice in Africa. 17. Managing the major diseases of rice in Africa. 18. Managing insect pests of rice in Africa. 19. Bird damage to rice in Africa: evidence and control. 20. Increasing rice productivity through improved nutrient use in Africa. 21. Assessing and improving water productivity of irrigated rice systems in Africa. 22. Inland valleys: Africa's future food baskets. Section 4. Rice value chain development. 23. Consumer preferences for rice in Africa. 24. Tailoring African rice value chains to consumers. 25. Improving grain quality of locally produced rice in Africa. 26. Developing competitive rice value chains. 27. Mechanizing Africa's rice sector. Section 5. Working with rice communities. 28. Integrating gender considerations in rice research for development in Africa. 29. Towards a new approach for understanding interactions of technology with environment and society in small-scale rice farming. 30. Innovative and effective ways to enhance rural learning in Africa. 31. Raising rice yields and beyond: an experience of collective l

The GLASS project (GLAberrima ASSembly), joint project between Institut de recherche pour le développement (IRD) and AfricaRice, aims to sequence de novo the two African NERICA parents, CG14 and TOG5681, representing the two extremes of Oryza glaberrima variability. For that purpose, we chose a hybrid approach combining the illumina high-quality short reads and the PacificBioscience Long Reads technology. Tests were performed using Illumina data on TOG5307 and TOG5681, using AbySS short-reads assembler, with 19x and 25x total data, respectively. For TOG5307, we obtained 153,774 contigs (minimum size of 200b), mean size of 1.5 kb (N50 = 2.4kb, N90 = 637b). On TOG5681, we obtained 97,196 contigs (minimum size 200b), with a mean size of 2.8kb (N50 = 5kb, N90 = 1.3 kb). The overall assembly for each genome is 0.56x for TOG5307 and 0.69x for TOG5681. Just adding +6x of Illumina data almost doubled the assembly efficiency. PacBio data test on C2 and XL kits were also performed for CG14 data, providing, respectively, 143,456 and 99,488 contigs (mean size of 3140b and 3184b), with a 1.12x and 0.79x coverage. The C2 10x sequencing in PacBio for CG14 and TOG5681, and the 60x sequencing in Illumina for each is underway. The annotation will be transferred from the Nipponbare MSU7.0 reference genome using tools such as QOD and BLAST/BLAT based scripts. These sequences will be immediately available for the whole community without restriction. The IRIGIN project from France Genomique (International RIce Genomic INitiative) is headed by IRD and Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), and aims to provide valuable genetic stocks genomic data in the frame of the Global Rice Science Partnership (GRiSP). African rice (300 O. glaberrima and 100 O. barthii) will be deeply resequenced (25x) and aligned on their reference (from the GLASS project). At the same time, NAMs population (indica x tropical japonica) from AfricaRice and the International Center for Tropical Agriculture (CIAT) will be genotyped (using low-coverage sequencing), to provide the best genetic map ever created in plants, with the highest level of coverage ever seen. Thousand of terabytes of raw data and billions of polymorphic data will be gathered within this project, and will be distributed to the whole rice community as soon as possible.

Madagascar Island was one of the last major Old World areas where human settlement was accompanied by the introduction of Oryza sativa. Early studies had reported the presence of a rice group specific to Madagascar. Using 1536 SNP markers, we compared diversity patterns between a panel of 147 Malagasy rice varieties, a reference panel of 370 Asian varieties and representatives of wild relatives of O. sativa. Migration bottleneck has resulted in 30-40% reduction of diversity among the indica and japonica groups in Madagascar. The Malagasy panel showed many fewer indica x japonica recombinations compared to the Asian panel, suggesting that the two groups had undergone much less recombinations when migration to the Island occurred. The existence of the Malagasy-specific group (Gm) was confirmed. Its diversity patterns positioned it halfway from indica and aus groups. Madagascar also hosted cold tolerant tropical japonica varieties, with very long grain. The Gm group most probably arose from founder effect from intermediary forms of rice originated from either India or Sri Lanka that did not belong to the four majors O. sativa groups. It then underwent human selection for cold tolerance. Signs of inter-group recombinations were also observed, but recombinations did not seem to have played a major role in the dynamics of rice adaptation to the Island's agro-ecological constraints. Connections between Gm and O. rufipogon from its putative area of origin reinforce the hypothesis of multiple and diffuse domestication of O. sativa as opposed to two independent domestications occurring in two distinct geographical areas. (Texte intégral)

Drought is one of the most important abiotic constraints that negatively impacts rice productivity, especially at reproductive stage. Developing drought-tolerant cultivars possessing high yield under a favorable water regime and fairly good yield under drought stress is crucial to sustain farmers' efforts in intensifying rice cropping systems. To develop such cultivars, we launched a marker-assisted recurrent selection (MARS) program, a new approach in rice breeding, where quantitative trait loci (QTLs) for the target traits are mapped within the progeny of elite materials with complementary traits, and favorable alleles of those QTLs are accumulated through successive cycles of intercrossing and genotyping-based selection. A population of 230 F3:5-derived lines from a cross between IR64 and B6144F, and 10 check varieties, have undergone 14 field evaluations for yield under favorable conditions (2 years) during the wet season, and five field evaluations for yield under cyclical drought during the dry season (one year) in five locations (Banfora, Burkina Faso; Longorola, Mali; Ibadan and Badeggi, Nigeria; Los Baños, Philippines and Santa Rosa, Colombia). The population was also evaluated for drought tolerance in a rain-out shelter (ROS), and also genotyped with 484 single nucleotide polymorphism (SNP) markers polymorphic between the two parents. A wide level of variability for target traits, irrespective of the water regime, was observed among the progenies in all locations. Under favorable conditions, the population average yield was 5.06 t/ha in Banfora, 4.19 t/ha in Badeggi, 4.08 t/ha in Ibadan, and 3.9 t/ha under the ROS. Three progenies out-yielded all the checks in Badeggi, and several yielded more than both parents. Similar variability was observed during the trials for drought tolerance. Yield reduction due to drought averaged 72.6%, 72%, 33% and 47%, under the ROS, in Ibadan, Longorola and Banfora, respectively. Stability estimated from environmental variance revealed that some lines (16 in Ibadan, 24 in Burkina Faso, 9 in Mali, 5 under ROS) had more stable yield than the best check. Seven QTLs related to yield under favorable conditions were detected on chromosomes 1, 3, 4 and 9 in Badeggi, Banfora and Longorola. The QTL on chromosome 3 (LOD = 4) explained 20.1 and 19.8% of the yield phenotypic variation in Banfora and Badeggi, respectively. This QTL is also related to plant height and days to flowering. In Ibadan and under the ROS, two QTLs for grain yield under drought stress, explaining 25.4% and 54.48% of the phenotypic variation, were detected. These results underline the successful development of a reliable phenotyping network. The next step will be to combine favorable alleles of those QTLs into a single line. A three-step optimization process is undertaken: first, the genetic value of F3 lines is estimated using genotypic data; second, a small set of candidate F3 lines is selected; third, the expected genetic value of their progeny is computed and crosses made. Improved material identified at each selection cycle will join the AfricaRice and NARS partners' varietal development and release pipelines. This is already the case for F3 lines with improved yield stability.

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. We investigated the accuracy of genomic estimate breeding values (GEBV) through cross validation in a synthetic population (SP) of broad genetic diversity developed for upland rice breeding for Latin America, through recurrent selection (RS). Three hundred and three S4 lines extracted from a SP that has undergone several RS cycles were phenotyped for flowering time (FL), plant height (PH) and grain weight per plant (GW), and genotyped with an average density of one marker per 22.9 kb, using genotyping by sequencing. Cross validation was performed hundred times, for four ratios of training and validation population sizes (TP/VP), using ridge regression best linear unbiased prediction (RR-BLUP), least absolute shrinkage and selection operator (LASSO) and Bayesian linear regression methods (BL). Accuracy was estimated as the correlation between GEBV and true breeding value. Linkage disequilibrium was high (average r²>0.5 at 20 kb; r²>0.25 at 1.5 Mb distance). Accuracy of GEBV increased with the size of the training population, regardless of the model. For FL and TP/VP varying from 150/153 to 270/33, the GEBV accuracy ranged from r=0.20 (0.05) to r=0.22 (0.15) under RR-BLUP, from r=0.19 (0.09) to r=0.28 (0.17) under LASSO, and from r=0.28 (0.03) to r=0.32 (0.17) under BL, before marker selection based on alleles frequency. GEBV accuracy was more sensitive to markers' allele frequency than to the total number of markers. The best selected S4 will be recombined and their progenies tested for GEBV accuracy across generations.

A collection of 312 accessions of Burkina Faso rice germplasm was evaluated in Cotonou, Benin and Montpellier, France for resistance using four Rice yellow mottle virus (RYMV) isolates. In Cotonou, the accessions were screened using one isolate from Benin (B27) and two isolates from Niger (Ng122 and Ng144). The experiment was conducted in a screenhouse. Fourteen-day-old plantlets were inoculated and symptoms scored fortnightly from 14 to 56 days after inoculation (dai). Plant height was recorded at 49 dai after all accessions were inoculated with isolates Ng122 and Ng144. Double Antibody Sandwich-Enzyme-Linked Immunosorbent Assay (DAS-ELISA) was used to assess RYMV into rice leaves. In Montpellier, aggressive isolate from Burkina Faso BF1 was used to assess the accessions against RYMV. The experiment was conducted in the greenhouse under controlled conditions (28-32°C, 12 h of light per 24 h and 80-90% relative humidity). Inoculation process and symptoms scoring were performed on rice leaves as in Benin and reverse-transcription polymerase chain reaction (RT-PCR) was used to check the presence of the allele rymvl -3 in resistant accessions. The results of both experiments showed that the Oryza sativa accessions of the collection were highly susceptible, except for BM24, which combined partial resistance and tolerance. Twenty-one O. glaberrima accessions out of 48 were resistant to Ng122 and Ng144. When these 21 accessions were subsequently screened with the aggressive RYMV strain BF1, eight of them displayed a delay in the appearance of RYMV symptoms, while two showed resistance. The molecular characterization of the resistant accessions showed that they do not have the allele rymvl-3. These accessions could have new resistance alleles. Therefore, the new sources of resistance identified in this study could be exploited in breeding to tackle the spread of RYMV in Africa.

Since 1992, we have been carrying out an upland rice breeding program for Latin American and the Caribbean based on the improvement of synthetic populations of broad genetic diversity through recurrent selection (RS). In this breeding scheme, at each RS cycle the population (Pn) is evaluated for specific traits and the selected units undergo recombination to generate the Pn+1 population and pedigree breeding to develop new and improved breeding lines. Recombination of the selected units is facilitated by the presence of recessive nuclear male-sterility. RS constitutes an effective framework for combining the centralised improvement of a small number of complex traits with decentralised breeding for site-specific traits. It has allowed us to provide our partners with improved lines and progenitors. We are now adapting our RS strategies to the availability of cheaper genotyping tools and high throughput and precision phenotyping platforms. Established from several cycles of recombination among a large number of founder accessions, synthetic populations make-up a valuable material for association analysis, with lower LD and improved mapping resolution compared to the RILs populations. This paves the way for implementation of marker assisted recurrent selection (MARS) aimed at continuous extraction of lines for specific environments while keeping genetic diversity for long term progress for complex traits. Synthetic populations also constitute a good material for genome-wide selection (GWS). We intend to compare the relative efficiency of different GWS schemes and MARS scheme for the improvement of yield potential and drought tolerance. (Texte integral)

Germplasm is the substrate used by plant breeders to create novel plant gene combinations and select crop varieties more suited to the needs of diverse agricultural systems. Crop germplasm diversity has been shaped by domestication, a complex anthropogenic process caused by a multitude of human populations with specific habits and needs. Genome analysis tools now provide access to thousands of polymorphisms, thus considerably enriching our approaches to the evaluation of diversity. This involves describing global diversity patterns, monitoring variations along the genome and investigating local sequence variation in regions of interest. The past few years have seen major progress in unravelling the drivers of crop evolution, including foundations, introgression, admixture, mutations, translocations, in a background of drift and selection. Results on rice, sorghum, banana, cacao, rubber tree, groundnut, among others, provide a range of situations which highlight targeted approaches to access the diversity conserved in ex situ germplasm collections and help build strategies for further germplasm collections. Soon it will be possible to determine and compare the whole sequence of hundreds of accessions. We therefore advocate identification for each important species of a common core set of reference materials to help R.E.A.D. (Represent existing diversity - Enter the whole collection - Assess phenotypic variation - Dissect trait-gene associations) germplasm through concerted efforts within the research community. This is being implemented by the Generation Challenge Programme (www.generationcp.org) of the CGIAR for the major food crops. The process of crop domestication is being analysed for a range of tropical crops by the Agropolis Resource Center for Crop Conservation, Adaptation and Diversity (www.arcad-project.fr) through a multidisciplinary approach associating ethnological studies to genomic surveys in search for selection signatures. This will help focus on specific germplasm compartments that enable high resolution genetic analyses in support for breeding as well as deploy renewed efforts for under-utilised species.

Rice is considered as a crop sensitive to salinity; however, it is grown mainly in deltaic areas with salt problems all over Europe. European rice breeding programs (France, Greece, Italy, Portugal and Spain) have established an European Rice Genetic Resources Collection (ERGRC) of some 450 accessions, mainly temperate japonica, extensively characterised for agronomic traits and maintained by CIRAD. The main goal of the present study is to identify within this collection, a set of best performing genes and alleles for salinity tolerance, as well as the associated donors and molecular markers for use in breeding programs. In order to obtain the general organisation structure of the ERGRC we assessed its genetic diversity through a Bayesian analysis of genotypic data over 26 SSR loci. A sub-sample of 200 accessions maximizing simultaneously allele number and allelic associations was then extracted for association analysis. The sub-sample was phenotyped for salinity tolerance at an early vegetative stage under controlled conditions, being leaf Na+/K+ ratio the most discriminating trait. Based on literature review, we assembled a list with more than 100 rice candidate genes for salt tolerance, which are involved in signaling, ion homeostasis, stress tolerance, transcription regulation, general metabolism and unknown functions. With this information, we developed a database of rice QTLs and candidate genes for salinity tolerance (http://tropgenedb.cirad.fr/html/rice_QTL.html). We selected 16 of these candidate genes for association analysis. SSR markers were used for the association analysis. A first set of 58 common SSR (www.gramene.org) covering these particular genes was used. In addition, we designed 320 SSR markers covering 100 kb up and downstream each candidate gene. In the end, we selected four of the designed SSR markers, the two closest to the gene and one in each end of the linkage disequilibrium region (100 kb each gene side). Results of association analysis between 16 target areas (using 60 SSR) and a dozen salinity tolerance traits are presented. Methodological constraints stem from the use of multi-allelic markers are discussed. (Texte intégral)

The general objective of the EU-funded EURIGEN project is the characterisation and exploitation of European ricegenetic resources of the temperate rice growing area, to enhance competitiveness of Europe in rice production, andalleviation of biotic and abiotic constraints typical of the Mediterranean area. This goal is achievable by means of theacquisition, evaluation and conservation of existing rice accessions, and identification of new genetic materials targetedat sustainable agricultural systems, making use of the most updated genomic tools. The project has two major targets: i)identification and conservation of genetic resources and ii) identification of valuable sources of new genes and alleles foragronomic and quality traits relevant to breeding programs. The main platform of the project is the classification,maintenance and regeneration of the temperate rice germplasm bank. A panel of 455 rice accessions relevant forbreeding programs in European growing areas were analysed at both phenotypic and genotypic level. A centralisedseed bank of the collection was established and a DNA biorepository organised in bar-coded 96-well plates was createdand made available to the EURIGEN partners. A core collection of 200 rice accessions was selected based uponphylogenetic analyses and phenotyped in the field and controlled conditions for adaptation to biotic and abiotic stressesincluding blast, reduced water availability and salinity. To identify molecular markers associated with the adaptation traitsas well as alleles ensuring the best performance under stress, the 200 accessions were genotyped with 384 SNPs usingthe high-throughput ILLUMINA BeadExpress genotyping platform. The SNPs were selected in candidate genes involvedin stress responses based on literature data and preliminary results from ongoing projects at international level. Theintegration of phenotypic and genotypic data will enable us to carry out association analyses and valorise the existingnatural variation to devise novel strategies of rice improvement in EU countries. The EURIGEN actions pursue thegeneral objectives in accordance with the assessments of the FAO International Treaty on Plant Genetic Resources forFood and Agriculture, and the Council Regulation (EC 870/2004) establishing a Community Programme on theconservation, characterization, collection and utilization of genetic resources in agriculture. (Texte intégral)