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Uganda lies within the drier end of the natural distribution range of Coffea canephora and contains unexplored genetic material that could be drought-adapted and useful for developing climate-resilient varieties. Using water treatment: (i) ample and (ii) restricted-water, the response of 148 genotypes were studied comprising wild, feral and cultivated C. canephora. Biomass allocation, standing leaf area and leaf area growth data were collected. Linear mixed effect models and PCA were used to the analyze effect of water treatment on genotypes from different: (i) cultivation status, (ii) genetic groups and (iii) locations. We also assessed the relationship between drought tolerance for relative growth rate in leaf area (RGRA), total number of leaves (TNL), total leaf area (TLA) and total leaf dry weight (TLDW) of genotypes at final harvest. Restricted-water reduced RGRA across genetic groups (3.2–32.5%) and locations (7.1–36.7%) but not cultivation status. For TNL, TLA and TLDW, genotypes that performed well in ample-water performed worse under restricted-water, indicating growth-tolerance trade-off. Drought tolerance in RGRA and TNL were negatively correlated with wetness index suggesting some degree of adaptation to local climate. Findings indicate a growth-tolerance trade-off within this tropical tree species and drought tolerance of Uganda's C. canephora is somewhat associated with local climate.

Understanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programs. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long-lived species such as trees. We conducted a population genomics study of 207 Coffea canephora trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defense pathways in coffee. Seventy-one SNPs were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like DREB-like and MYB family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, like the DXMT gene involved in caffeine biosynthesis and a putative pest repellent. These climate-associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of ex-situ conservation strategies are discussed., Understanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programs. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long-lived species such as trees. We conducted a population genomics study of 207 Coffea canephora trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defense pathways in coffee. Seventy-one SNPs were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like DREB-like and MYB family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, like the DXMT gene involved in caffeine biosynthesis and a putative pest repellent. These climate-associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of ex-situ conservation strategies are discussed.

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 vita

Coffea canephora Pierre ex A. Froehner (Robusta coffee) is an important crop sustaining millions of livelihoods in its production zone which is predominated by poor countries. Like the other commercially important coffee species, Coffea arabica, the production of Coffea canephora is threatened by the prevailing intense and frequent drought spells reported to be increasing in relation to climate change. There is thus an urgent need to develop drought resilient C. canephora cultivars especially for poor farmers who often lack irrigation options. Availability of C. canephora intraspecific diversity and occurrence of wild populations across an environmental gradient may indicate presence of valuable genetic material, which could be used directly as a new variety or as a parent in breeding climate resilient varieties. This thesis explored: (i) the genetic diversity of Ugandan Robusta coffee; (ii) linkages between allelic variation and environmental variables; (iii) phenotypic variation in drought tolerance and (iv) phenotypic plasticity to shifts in water availability and its relationship with drought tolerance. Results showed that: Uganda’s C. canephora differentiates into five geographically delimited groups, and there is substantial phenotypic variation in relation to their response to water availability across locations and genetic groups but no significant phenotypic variation along the level of cultivation status. We observed a trade-off between drought tolerance and growth in ample water conditions. Drought tolerance of the genotypes was negatively associated to an index that indicated wetness of the climate at their locations suggesting some degree of local adaptation. Finally, our results also showed a negative correlation between plasticity in response to changes in water availability and drought tolerance. Generally, our study revealed the comprehensive genetic structure of Uganda’s C. canephora, its differential response in to drought stress, growth-tolerance

A captura direcionada de sequências acoplada ao sequenciamento de alto rendimento tornou-se um método poderoso para o estudo da variação de sequências genômicas. Usando o genoma disponível de C. canephora (tamanho estimado de 710 Mb/haplóide) como referência, projetamos sondas para 323 genes candidatos selecionados (CGs) visando capturar seus homeólogos em 293 acessos de C. canephora da Uganda, 12 clones do Brasil e um subconjunto de 19 indivíduos cobrindo todos os grupos de diversidade de C. canephora. Para um total de 324 indivíduos de C. canephora, projetamos, com sucesso, cerca de 19.000 sondas e identificamos mais de 16.000 polimorfismos de nucleotídeo único (SNPs) de qualidade, localizados dentro ou próximo a 318 genes anotados, gerando dados genotípicos para populações que estão localizadas em regiões que abrangem diferentes condições climáticas. Nós investigamos questões como desenho das sondas, cobertura do sequenciamento, eficiência da hibridização e captura, e estratégias de análise dos dados por bioinformática.

Testar se e como populações naturais são adaptadas ao seu ambiente local e prever suas respostas em função das alterações futuras do habitat é de importância fundamental diante do cenário de mudanças climáticas. Este é o caso dos cafeeiros, em que o ritmo das alterações climáticas pode ser rápido e drástico para a adaptação das populações. Usando a distribuição geográfica de populações selvagens com habitats contrastantes, o objetivo do presente estudo foi identificar polimorfismos de nucleotídeo único (SNPs) em genes candidatos (GCs) identificados como estando envolvidos na adaptação de populações de Coffea canephora da Uganda ao seu ambiente local. Em particular, modificações que ocorrem próximos e/ou em genes relacionados à tolerância aos estresses abióticos tornam esses GCs alvos, potenciais determinantes adaptativos das plantas em função das mudanças climáticas. Ao identificar os fatores ambientais que impulsionam esses processos, torna-se possível prever a adaptabilidade esperada das populações para o clima local futuro.

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 (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 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 SNPs 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 SNPs (~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 SNPs 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.

ln the light of adaptation, understanding how organisms respond to their environment, by altering physiological processes, will increase our capacity to make predictions about adaptation to global climate change. Adaptive dines have been increasingly studied in plant species within temperate zones to understand adaptation of organism in natural populations. However, they are still poorly understood in tropical environments. Coffea canephora, cultivated as Robusta, is an interesting tropical tree model to investigate adaptation in the tropics as it is largely distributed within the range of the lowland tropical rain forests of Africa. ln particular, modifications occurring in genes related to abiotic stress tolerance make these genes candidate for enhanced resilience to future climate change. We combined the use of bath captured regions sequenced for a set of candidate genes related to drought tolerance and whole genome SNP markers. Leveraging on a robust statistical approach combining multiple neutrality statistics, we provided a comprehensive map of selection signais in the genome of the C. canephora bath at the species level and within its major genetic groups. The genotype-environment association suggests regional adaptation to spatially varying environments of the recent past, with a special focus on the Eastern edge of the distribution, in Uganda. More specifically, we found signais of selection tightly linked to several genes involved in response to biotic and abiotic stress and in caffeine biosynthesis. Our detection of selection signais support the hypothesis of present ecological gradient contributing to the structure of the genetic diversity. Moreover, assessing the genomic vulnerability of the present populations will help to predict their response to future environmental changes.