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The NitroSorg project is funded by CASDAR, Ministère de l'Agriculture et de l'Alimentation, France. It involves INRAE and CIRAD through the participation of the AGAP, IATE, BOA research units and the PEAT Experimental Unit, the Eurosorgho and RAGT2n seed companies, and the technical institute ITAVI. Although the SELMET research unit does not benefit directly of financial support of the project, it provides its expertise on feed quality phenotyping tools to the consortium. Nitrosorg will begin in 2022 and will last 42 months. It brings together a multidisciplinary consortium of biologists, geneticists, breeders, biochemists and poultry feed specialists to better understand the establishment of sorghum grain quality for poultry feeding and contribute to the development of breeding tools to optimize breeding efficiency for this target. Indeed, the low digestibility of sorghum grain proteins by gastrointestinal proteases, which has the particularity of decreasing even further after cooking, represents an important obstacle to a wider use of sorghum for feed but also for human nutrition. This low digestibility can be attributed to the interaction of proteins with other grain compounds such as starch or tannins, but is mainly related to the structure and properties of the storage proteins of sorghum grain (kafirins). One of the objectives of this project is to develop high-throughput characterization tools for the protein content and digestibility, but also starch and tannin content and endosperm texture that can affect this digestibility. The consortium will mobilize these tools to characterize the current European varietal offer, a panel representing the worldwide diversity, and the parental lines of the partner's breeding programs. Finally, we will carry, on a smaller panel of genotypes, an analysis of kafirin composition, and an exhaustive analysis of in vitro and in vivo protein digestibility (as part of poultry feeding). These analyses should allow us to assess the relevance of the high-throughput screening tools developed and will lead to the definition of the target ideotypes for poultry feeding. In the long term, these results will contribute to the development of grain sorghum varieties with a better protein content and digestibility, and therefore an improved nutritional value.

International audience; Background: The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Results: Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). Conclusions: This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.

With the decreasing cost of genome sequencing, many laboratories are increasingly adopting genotyping technologies as a routine component of their analytical workflows, generating large datasets (e.g. VCF files) of genotyping information. Nevertheless, manipulating such large datasets remains a challenge for many scientists. In this context, we developed Gigwa (Genotype Investigator for Genome-Wide Analyses) with the aim of providing a user-friendly system to meet the requirements of scientists who need to filter large datasets and export them into various formats for subsequent analyses. Gigwa is species-agnostic, cross-platform, scalable and easy to deploy. It can be configured to run on a local computer or setup across servers to act as a data portal. It may be used to share data with collaborators while providing means to seek variants of interest based on location, functional annotations or genotype patterns. Based on NoSQL technology, it supports very large datasets (up to tens of millions of genotypes) when configured on suitable hardware. Its most attractive features are: ergonomic interface including user management, numerous import and export formats, powerful filtering engine, interoperability via REST APIs and connection to online or standalone tools. Gigwa now in version 2 (http://gigwa.southgreen.fr), is developed within the scope of South Green bioinformatics, a cross-institute platform and community dedicated to genetics and genomics of tropical and Mediterranean plants, based in Montpellier, France.

International audience; The ascomycete filamentous fungus Neurospora crassa played a historic role in experimental biology and became a model system for genetic research. Stimulated by a systematic effort to collect wild strains initiated by Stanford geneticist David Perkins, the genus Neurospora has also become a basic model for the study of evolutionary processes, speciation, and population biology. In this chapter, we will first trace the history that brought Neurospora into the era of population genomics. We will then cover the major contributions of population genomic investigations using Neurospora to our understanding of microbial biogeography and speciation, and review recent work using population genomics and genome-wide association mapping that illustrates the unique potential of Neurospora as a model for identifying the genetic basis of (potentially adaptive) phenotypes in filamentous fungi. The advent of population genomics has contributed to firmly establish Neurospora as a complete model system and we hope our review will entice biologists to include Neurospora in their research.

Understanding the genomic and ultimate eco-evolutionary factors underlying the diversification of fungal organisms is a major goal for evolutionary mycologists, and a key step towards comparative eukaryotic speciation genetics. Access to whole-genome sequences and advanced computational methods provide mycologists with powerful tools to disentangle the complex evolutionary history of fungi. Speciation genomics approaches based on the application of population genomic models at the intra- inter-specific boundary are changing our view of the factors and mechanisms underlying fungal diversification, revealing that processes such as introgression, hybridization, rapid speciation, and horizontal gene transfer had been overlooked. The filamentous fungus Neurospora is an emerging model to study fungal speciation. Neurospora discreta PS4, in particular, has a very large distribution and is therefore an ideal system to investigate the eco-evolutionary drivers and genomic correlates of fungal diversification. Previous studies have shown deep population structure within N. discreta PS4 with limited admixture, but the structure of the species at finer scale, and the extent of admixture and gene flow between lineages remains unclear. Here, we used re-sequencing of 128 isolates representing 17 sites in Europe, North America and Asia to infer the evolutionary history of N. discreta PS4. We confirmed the existence of five lineages; one in Papua New Guinea, one in Thailand and three in USA and Europe, and found a new lineage distributed in both Portugal and Washington (USA). Our analyses reveal deep divergence between lineages, with virtually no admixture. Most sampled sites harbored only a single lineage of N. discreta PS4 but at least five sites harbored two or three lineages coexisting in sympatry without evidence for genetic mixing. We discuss the factors that may have contributed to the divergence of lineages, their co-occurrence in sympatry, and their maintenance without admixture.

To face global warming and fossil fuel depletion crisis, plant biomass will provide a renewable source of energy, materials and chemicals. Accordingly, agriculture will have to adapt not only to avoid competition between food-feed and non-food non-feed uses but also to ensure the economical and environmental sustainability of these productions. In this context, we are developing an integrative strategy merging genetics, breeding, material sciences, energy production, animal nutrition and socio economic analyses to accelerate the development of multipurpose sorghum value chains for both Mediterranean and tropical semi-arid conditions (West Africa). As a first step, new products (biocomposites) and uses (biomethane production) are being developed. Then the plant traits impacting the production and quality of the different end-products and uses are being identified taking advantage of the genetic diversity of sorghum. As a third step, the set-up of these key traits in the plant is being analyzed in order to describe their patterns of development / accumulation, their susceptibility to environmental constraints and provide some insights regarding their molecular determinism. Taking advantage of these functional information, the genomic regions impacting the key traits are being deciphered and used to develop new breeding tools and breeding strategies. In parallel, to maximize the probability to convert scientific results in local impacts, the different stakeholders of the value chains are being mobilized and territorial analyses aiming to assess the relevance of the different value chains are performed.

It is well known that drought periods affect coffee plant development, leading to plant death and abortion of developing fruits in case of severe drought. In relation to coffee genetic diversity, several works reported the identification of plants of C. canephora conilon susceptible or tolerant to drought which were analyzed at the physiological level and also used to identify candidate genes underlying stress responses. Even narrow, a genetic diversity for drought tolerance also exist in the species C. arabica. In addition to the identification of undiscovered transcripts, the recent development of low-cost, high throughput next-generation (NGS) sequencing technologies now opens the way to perform expression profiling and to identify gene presenting differential expression patterns by comparing the frequency of reads obtained after sequencing. In order to initiate such kind of approach in coffee, RNA of meristematic tissues from Iapar59 (I59, drought tolerant) and Rubi (R, drought sensible) cultivars of C. arabica grown under field-grown with (I) or without (NI) irrigation were extracted and used to generate cDNA that were further sequenced. The sequencing data revealed 282.213, 135.304, 345.751 and 230.064 reads obtained from I59-I, I59-NI, R-I and R-NI samples, respectively, totalizing more than 255Mb. These data was compared with all available transcriptome Coffea data, including the EST sequences from both Coffea arabica and C. canephora. The results of these comparisons will be presented as well as the preliminary data of an electronic northern performed in order to identify differentially expressed genes between the two cultivars in both conditions (NI or I). General numbers show that Rubi has a more intense molecular response to drought, with many genes over-expressed. Also functional analysis of biological processes shows an enrichment of stress response genes in Rubi non-irrigated while in I59 there is a decrease in expression in genes related to carbohydrate metabolism and cell wall organization. It is worth noting the number of genes up-regulated in Rubi non irrigated (NI) and involved with drought stress response, like RD22, PDIR10 (dirigent-like protein), MYB and caffeine synthase for example, while these genes were not detected under this stress in I59. In other hand, many drought genes related to drought-stress tolerance were detected in the I59 cultivar involved in biosynthetic process such as sugar transporters, some proteins related with abiotic stress tolerance (i.e. osmotins), water channel protein, LEA proteins (implicated in detoxification and alleviation of cellular damage during dehydration) and heat shock proteins (HSPs). In the I59 cultivar, genes coding for enzymes involved in the ABA synthesis (isopentenyl diphosphate isomerase, geranylgeranyl reductase), which causes stomatal closure, precursor and enzymes, were also 1 highly expressed. Q-PCR experiments were also performed and allowed to confirm the data obtained in silico for several genes. These results will be presented and discussed.

The genetic diversity of C. arabica in Ethiopia, its region of origin, was explored. Its use for C. arabica breeding, though limited to a few F1 crosses with cultivars, proved to be efficient in terms of genetic gain regarding important coffee agronomic characteristics such as vigor, adaptability and quality. A collection derived from the 1964-65 FAO survey in Ethiopia was established at IAPAR in Londrina, PR, Brazil in 1976. Genotyping was undertaken using SSR markers that were polymorphic within these accessions. Preliminary results regarding the relation between genetic and phenotypic diversity are presented. Self pollinated progenies of 179 plants representing 115 Ethiopian accessions were established at IAPAR, from 2009 to 2012. 47 of them were also established at CPAC, DF. Various growth parameters were measured.

Drought is a key factor affecting coffee plant development and production. In the context of global warming, the generation of drought-tolerant coffee varieties has now turned into one of the priorities of many coffee research institutes. At the genetic level, it is well known that variability exists within the Coffea genus regarding the tolerance to drought-tolerant. During the last decade, several drought-tolerant clones of C. canephora Conilon have been characterized as vigorous plants with high productivity throughout years under drought stress. Physiological analyses suggested that drought tolerance could be a direct consequence of better root development or of enhanced activity of antioxidant enzymes. The recent advances in coffee genomics mainly expressed sequence tag (EST) sequencing projects now open the way to study the molecular and genetic determinism of drought tolerance and to the identification of molecular markers that could be used to speed up coffee breeding programs. With the aim to investigate the molecular mechanisms underlying drought tolerance in coffee plants of C. canephora and C. arabica, qPCR experiments identified more than 80 candidate genes (CGs) presenting differential gene expression between drought-tolerant and drought-susceptible clones/cultivars cultivated under different (with or without) irrigation conditions. Based on the results obtained in C. canephora, we concluded that factors involved a complex network of responses probably involving the abscisic (ABA) signaling pathway and nitric oxide (NO) are major molecular determinants that might explain the better efficiency in controlling stomata closure and transpiration displayed in drought-tolerant clones. In the drought-tolerant I59 cultivar C. arabica, many CGs involved in the signal transduction pathway of drought stress but also in the synthesis of several biochemical compounds (derivative-sugars etc...), were highly over-expressed under drought compared to drought-susceptible Rubi cultivar. We also identified several CGs that do not exhibit any similarity with those already deposited in global databases and commonly called "no hits". Recent concepts, called these "no hits" as "orphan genes" and postulate that the emergence of these are the result of adaptive responses specific to each species as a function of stresses and adverse conditions faced by these plants during the evolutionary process. This work presents data of expression profiles obtained for several CGs and some orphan genes (called CcUnk [Unknown]) and discussed their putative role in coffee responses to abiotic stress. Work supported by CAPES-COFECUB, CIRAD, Consórcio Pesquisa Café and INCT-Café (CNPq/FAPEMIG). (Texte intégral)

Para estudar os mecanismos moleculares envolvidos na resistência à seca em plantas de café, meristemas de ramos plagiotrópicos dos cultivares de Coffea arabica, IAPAR59 (I59 - planta com provável resistência à seca) e Rubi (R - planta com pouca resistência à seca) crescidas em condições normais (I) e de estresse hídrico (NI) foram coletados e usados para construção de bibliotecas de cDNA que foram sequenciados usando a plataforma GS-FLX Titanium da Roche. Após tratamento dos dados brutos, foram obtidas 207.516, 109.005, 250.413 e 173.693 reads das amostras de I59-I, I59-NI, R-I e R-NI, respectivamente, totalizando mais de 255 Mb. Todas essas bibliotecas foram mapeadas no transcriptoma de Coffea arabica para identificação indireta da expressão de cada gene para cada condição. Do transcriptoma total formado por 55578 contigs, 48730 contigs tiveram reads mapeados e 7899 novos contigs foram formados. Com o banco de dados é possível identificar genes e grupos de genes expressos exclusivamente por uma espécie ou outra, em condição de estresse hídrico ou não. Esses são os primeiros dados de meristema de café submetidos a estresse hídrico, os resultados dessa comparação serão apresentados como dados preliminares de um northern eletrônico para identificação de genes diferencialmente expressos em ambos os cultivares em ambas as condições.

In order to study the molecular mechanisms underlying the response to drought stress in coffee plants, meristems of plagiotropic branches from Iapar59 (I59, drought tolerant) and Rubi (R, drought susceptible) cultivars of Coffea arabica grown in field-grown conditions and submitted (NI: non-irrigated) or not (I: irrigated) to water stress were collected at the end of the dry season and used to generate cDNAs that were sequenced using the GS-FLX Titanium strategy. The crude analysis of sequencing data revealed 282.213, 135.304, 345.751 and 230.064 reads obtained from I59-I, I59-NI, R-I and R-NI samples, respectively, totalizing more than 255Mb. For both experiments, most of the reads (>65%) had high quality and were assembled to generate around 24.000 contigs with an average length above 500pb. These data, which are the first one coffee meristems subjected to water stress, will be compared with all available transcriptome Coffea data, including the EST sequences from both Coffea arabica and C canephora. The results of these comparisons will be presented as well as the preliminary data of an electronic northern performed in order to identify differentially expressed genes between the two cultivars in both conditions (NI or I).

Coffee is one of the most important cash crops for numbers of countries in the intertropical zones all over the world. Coffea canephora is responsible for about 35% of the total world production of coffee. Natural area of this species corresponds to the actual zone of tropical rainforest in Africa. In order to better assess genetic resources and natural history of this species, we analysed a sample of 285 individuals from different sampling points on the repartition area, including some cultivated genotypes. A set of 39 nuclear microsatellites markers was genotyped in order to investigate species genetic structure and population history. An integrate approach combining both distances (factorial analysis) and bayesian model (Structure) methods was used to study the species structure. We shown that 2 major groups can be clearly discriminated, those two groups correspond to previous work led by Berthaud. However a finest structure has been shown, dividing the previous groups in a total of 6 groups, whereas previous studies have shown 5). We tried to investigate those groups history by computing the dm² statistic of Goldstein in our sample. Results show the possible effect of glaciation refuge areas on the elaboration of the Coffea canephora genetic structure, separating a guinean region composed by 2 groups and a Congolese one composed by four groups.

Research for genetic improvement still lacks adequate core germplasm for improving C. canephora quality, consequently farmers lose more of their incomes particularly in severe world coffee price crisis. Also the great range of variation within the Ugandan C. canephora has clearly been recognised but no attempt, however, has been made to differentiate the components at DNA level. In our study, samples were collected as seed and cuttings from farms Kawanda germplasm collection. Species diversity was evaluated using Sequence Repeats (S SR), Near Infra Red spectroscopy, (NIRS), biochemical titrations and cup testing after roasting. Controls were from known genetic diversity groups of C. canephora. A diversity tree was constructed with SSR polymorphism by Neighbour Joining (NJ) analyses from dissimilarity matrix. DNA results pointed out three major groups of farm trees with one group constituting of entries from closely located districts and controls a distinct group of their own. Four groups were derived from NIRS analyses of fruits with Erecta types forming own group and collections from mainly one district comprising another. Ugandan genotypes were also noted to have high sucrose and fat content with cup test analysis confirming that Ugandan robustas are better than most other robustas. No significant difference between NIRS and biochemical analysis for caffeine offer opportunity for analysing samples from more districts and Kawanda collection using NIRS because it is fast and cheaper. Use of DNA, NIRS, biochemical and cup test analyses in correlation with the environmental information offer opportunity for selecting entries with good quality that will promote sustainable development of the coffee growing areas by generating a reliable market.

Coffea genus includes more than 80 taxa, representing a high genotypic and phenotypic diversity. Our study leads to an evaluation of diversity, based on two types of markers, microsatellites (SSR) and Single Nucleotide Polymorphisms. Coffea diversity was evaluated at two levels: 20 species of the genus were analysed whereas a wider sampling was performed for Coffea canephora. 60 SSR markers were used; they provided new information concerning Coffea genus structuration and phylogenetic relationships between species. At the interspecific level, results are consistent with the geographical distribution of species. Within C. canephora, the knowledge of the genetic diversity of wild and cultivated populations is important as preliminary information for genetic improvement. Results obtained are consistent with previous studies. Furthermore, a new group including the Ugandan genotypes was identified, constituting the most eastern located independent genetic group, with a level of diversity comparable to Congolese genotypes. Analyses on SNPs diversity have also been performed for some specific genes implicated in sucrose and diterpen metabolisms. Results give complementary data on diversity, and indicate if these genes were subjected to natural of artificial selection, indicating the best putative candidate genes. Consequences for the identification of tools for Marker Assisted Selection are discussed.

In the current context of overproduction and low prices, coffee producers give a particular attention to coffee quality, impact on human health being one of its components. In this context, diterpens content constitutes a relevant target trait (Cavin et al., 1998). Coffee diterpens (Cafestol, Kahweol and 16-O-Methylcafestol) are specific of the coffee genus(Finnegan et Djerassi, 1960; Speer and Mischnick, 1989). Little information is available on coffee diterpens metabolism. Today only the enzymes implied in the way of biosynthesis of Ent-Kaurene are known. The ultimate stages between Ent-Kaurene and Cafestol, Kahweol, 16-O-MC are not identified yet.

Quality and drought stress tolerance are two important targets for Coffea species cultivation. Currently, efficient genetic improvement of these traits is still hampered by the lack of early and cheap predictors. In this context, identification of molecular tools linked to these traits would significantly improve breeding efficiency. Based on the available literature, different metabolisms involved in the variability of both drought tolerance and coffee quality can be proposed. Based on this information, a study was initiated in Coffea species, aiming at estimating nucleotide diversity of four sucrose metabolism enzymes (Sucrose Synthase, Cell Wall Invertase, acid Vacuolar Invertase and Sucrose Phosphate Synthase). The two mains objectives of this work were i) to assess the level of variability of these genes within the whole area of distribution of Coffea canephora, and within 15 related Coffea species representing the four groups of diversity of this genus, and ii) to identify polymorphisms useful for mapping and association genetic studies. Almost 200 polymorphisms (SNP, INDELS, SSR) were identified through sequencing of Coffea canephora genotypes. In addition, analysis of the variability of these genes between different Coffea species allowed the identification of 300 additional polymorphic sites. Parallel in-silico analysis of EST resources confirmed the interest of this approach towards the identification of polymorphisms in Coffea sp. Identification of nucleotide polymorphisms will not only provide useful markers for traditional genetic studies (genetic mapping, population genetics, association studie) but also provide criteria to infer the evolutionary history of the analysed genes. Such information will be particularly relevant to select the best candidate genes to test in future association studies.

Coffee wilt disease (CWD) caused by Fusarium xylarioides appeared in 1993 in Uganda and has become a serious problem of coffee production. From the 1940's to 1960's the disease caused considerable destruction to C. canephora in Central and West Africa. This disease was effectively controlled by uprooting and planting resistant varieties. For developing wilt resistant varieties in Uganda, wild Coffea canephora trees from Kibale and Itwara primary forests were studied together with cultivated genotypes of nganda and erecta phenotypes and other cultivated genotypes from Kalangala Islands in Lake Victoria. The genotypes were analyzed for genetic diversity using 24 SSR markers covering many parts of C. canephora genome. These studies found significant genetic differences between Kibale, Itwara, Kalangala and a group constituted of nganda and erecta genotypes. A comparison of Ugandan genotypes with known C. canephora diversity groups using 18 of the SSR markers revealed that Ugandan genotypes constitute a new diversity group in the species. Therefore it was interesting to test this Ugandan material for resistance to coffee wilt disease. Resistances tests were performed using a field isolates of Fusarium xylarioides on open pollinated progenies of some of Kibale, Itwara, Kalangala and Nganda and erecta individuals studied for genetic diversity. Results of these tests revealed presence of resistance among genotypes from all sources and significant genetic differences between sources. High variability between progenies within each source was also detected. In this paper importance of this diversity in developing improved coffee varieties is discussed.

Robusta coffee, produced by Coffea canephora, represents about 35% of the world coffee production. As part of studies aiming at the improvement of coffee cup quality, the knowledge of the genetic diversity of the wild and cultivated populations is an important task. Up to 210 individuals from different geographic origin were screened for diversity with a set of microsatellites markers take from the whole genome. The results of this analysis are consistent with the previous studies made with other kind of markers (RFLP and isozymes). Several genetic parameters were computed and indicate a very high diversity and structuration of the species. Original wild material from Uganda (1) was also studied in order to replace it within the previously known groups. Several genetic parameters (e.g. PIC, F statistics) were computed in order to better know the dynamic of these populations. These results will be discussed in the context of Coffea canephora genetic improvement.

The objective of this study was to precise the known diversity in this genus with a whole genome coverage microsatellite set. Microsatellites markers derived from three different origins (SSR enriched library, gene sequences and BAC library?) were applied to a set of 45 individuals representing 20 species. The aim of this work was to validate with a large set of microsatellites previous diversity studies made with other markers (RFLP, isozymes) and to relocate the genetic diversity of C. canephora in a global context. Our results clearly validate the previously described geographic groups of the Coffea genus. Considering the rapid evolution of microsatellites, the genome organisation and the origin of the C. Arabica genome is discussed. Moreover, the interspecific transferability of microsatellites defined on a specific species was very good. The focus made on several species allowed us to make some comparisons on several genetic parameters e.g. PIC and mean number of alleles. The results and the future work on the basis of this set of markers and individuals are discussed.