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Wild genetic resources and their ability to adapt to environmental change are critically important in light of the projected climate change, while constituting the foundation of agricultural sustainability. To address the expected negative effects of climate change on Robusta coffee trees (Coffea canephora), collecting missions were conducted to explore its current native distribution in Uganda over a broad climatic range. Wild material from seven forests could thus be collected. We used 19 microsatellite (SSR) markers to assess genetic diversity and structure of this material as well as material from two ex-situ collections and a feral population. The Ugandan C. canephora diversity was then positioned relative to the species’ global diversity structure. Twenty-two climatic variables were used to explore variations in climatic zones across the sampled forests. Overall, Uganda’s native C. canephora diversity differs from other known genetic groups of this species. In northwestern (NW) Uganda, four distinct genetic clusters were distinguished being from Zoka, Budongo, Itwara and Kibale forests A large southern-central (SC) cluster included Malabigambo, Mabira, and Kalangala forest accessions, as well as feral and cultivated accessions, suggesting similarity in genetic origin and strong gene flow between wild and cultivated compartments. We also confirmed the introduction of Congolese varieties into the SC region where most Robusta coffee production takes place. Identified populations occurred in divergent environmental conditions and 12 environmental variables significantly explained 16.3% of the total allelic variation across populations. The substantial genetic variation within and between Ugandan populations with different climatic envelopes might contain adaptive diversity to cope with climate change. The accessions that we collected have substantially enriched the diversity hosted in the Ugandan collections and thus contribute to ex situ conservation of this vital genetic resource. However, there is an urgent need to develop strategies to enhance complementary in-situ conservation of Coffea canephora in native forests in northwestern Uganda.

Summary Coffee species such as Coffea canephora P. (Robusta) and C. arabica L. (Arabica) are important cash crops in tropical regions around the world. C. arabica is an allotetraploid (2 n = 4 x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2 n = 2 x = 22). Interestingly, these progenitor species harbour a greater level of genetic variability and are an important source of genes to broaden the narrow Arabica genetic base. Here, we describe the development, evaluation and use of a single‐nucleotide polymorphism ( SNP ) array for coffee trees. A total of 8580 unique and informative SNP s were selected from C. canephora and C. arabica sequencing data, with 40% of the SNP located in annotated genes. In particular, this array contains 227 markers associated to 149 genes and traits of agronomic importance. Among these, 7065 SNP s (~82.3%) were scorable and evenly distributed over the genome with a mean distance of 54.4 Kb between markers. With this array, we improved the Robusta high‐density genetic map by adding 1307 SNP markers, whereas 945 SNP s were found segregating in the Arabica mapping progeny. A panel of C. canephora accessions was successfully discriminated and over 70% of the SNP markers were transferable across the three species. Furthermore, the canephora‐derived subgenome of C. arabica was shown to be more closely related to C. canephora accessions from northern Uganda than to other current populations. These validated SNP markers and high‐density genetic maps will be useful to molecular genetics and for innovative approaches in coffee breeding.

Coffea canephora breeding requires combining sustainable productivity with improved technological and cup quality characteristics. Beverage quality is a complex and subjective trait, and breeding for this trait is time consuming and depends on knowledge of the genetics of its components. A highly variable C. canephora progeny resulting from an intraspecific cross was assessed for 63 traits over 5 years. To identify quantitative trait loci (QTLs) controlling agronomic, technological, and quality-related traits, a genetic map comprising 236 molecular markers was constructed, and composite interval mapping was performed. Beverage quality was evaluated in relation to biochemical and cup tasting traits. QTLs were identified for almost half of the traits evaluated, with effects ranging from 6% to 80% of phenotypic variation. Most of them present a consistent detection over years. The strongest QTLs explained a high percentage of the variation for yield in 2006 (34% to 57%), bean size (25% to 35%), content of chlorogenic acids (22% to 35%), sucrose and trigonelline content (29% to 81%), and acidity and bitterness of coffee beverages (30% to 55%). Regions of the C. canephora genome influencing beverage quality were identified. Five QTL zones were co-localized with candidate genes related to the biosynthesis of the analyzed traits: two genes coding for caffeine biosynthesis, one gene implicated in the biosynthesis of chlorogenic acids, and two genes implicated in sugar metabolism. This is one of the first studies on the identification of QTLs combining agronomic and quality Communicated by D. GrattapagliaElectronic supplementary material The online version of this article (traits in coffee. The high variability of quality traits within C. canephora and the presence of consistent QTLs offer breeders a promising tool to improve coffee cup quality.

The management of diversity for conservation and breeding is of great importance for all plant species and is particularly true in perennial species, such as the coffee Coffea canephora. This species exhibits a large genetic and phenotypic diversity with six different diversity groups. Large field collections are available in the Ivory Coast, Uganda and other Asian, American and African countries but are very expensive and time consuming to establish and maintain in large areas. We propose to improve coffee germplasm management through the construction of genetic core collections derived from a set of 565 accessions that are characterized with 13 microsatellite markers. Core collections of 12, 24 and 48 accessions were defined using two methods aimed to maximize the allelic diversity (Maximization strategy) or genetic distance (Maximum-Length Sub-Tree method). A composite core collection of 77 accessions is proposed for both objectives of an optimal management of diversity and breeding. This core collection presents a gene diversity value of 0.8 and exhibits the totality of the major alleles (i.e., 184) that are present in the initial set. The seven proposed core collections constitute a valuable tool for diversity management and a foundation for breeding programs. The use of these collections for collection management in research centers and breeding perspectives for coffee improvement are discussed.