Crop-to-wild gene flow in wild coffee species: the case of Coffea canephora in the Democratic Republic of the Congo.

BACKGROUND AND AIMS: Plant breeders are increasingly turning to crop wild relatives (CWRs) to ensure food security in a rapidly changing environment. However, CWR populations are confronted with various human-induced threats, including hybridization with their nearby cultivated crops. This might be a particular problem for wild coffee species, which often occur near coffee cultivation areas. Here, we briefly review the evidence for wild Coffea arabica (cultivated as Arabica coffee) and Coffea canephora (cultivated as Robusta coffee) and then focused on C. canephora in the Yangambi region in the Democratic Republic of the Congo. There, we examined the geographical distribution of cultivated C. canephora and the incidence of hybridization between cultivated and wild individuals within the rainforest. METHODS: We collected 71 C. canephora individuals from home gardens and 12 C. canephora individuals from the tropical rainforest in the Yangambi region and genotyped them using genotyping-by-sequencing (GBS). We compared the fingerprints with existing GBS data from 388 C. canephora individuals from natural tropical rainforests and the INERA Coffee Collection, a Robusta coffee field gene bank and the most probable source of cultivated genotypes in the area. We then established robust diagnostic fingerprints that genetically differentiate cultivated from wild coffee, identified cultivated-wild hybrids and mapped their geographical position in the rainforest. KEY RESULTS: We identified cultivated genotypes and cultivated-wild hybrids in zones with clear anthropogenic activity, and where cultivated C. canephora in home gardens may serve as a source for crop-to-wild gene flow. We found relatively few hybrids and backcrosses in the rainforests. CONCLUSIONS: The cultivation of C. canephora in close proximity to its wild gene pool has led to cultivated genotypes and cultivated-wild hybrids appearing within the natural habitats of C. canephora. Yet, given the high genetic similarity between the cultivated and wild gene pool, together with the relatively low incidence of hybridization, our results indicate that the overall impact in terms of risk of introgression remains limited so far.

Genetic diversity and structure in wild Robusta coffee (Coffea canephora A. Froehner) populations in Yangambi (DR Congo) and their relation to forest disturbance.

Degradation and regeneration of tropical forests can strongly affect gene flow in understorey species, resulting in genetic erosion and changes in genetic structure. Yet, these processes remain poorly studied in tropical Africa. Coffea canephora is an economically important species, found in the understorey of tropical rainforests of Central and West Africa, and the genetic diversity harboured in its wild populations is vital for sustainable coffee production worldwide. Here, we aimed to quantify genetic diversity, genetic structure, and pedigree relations in wild C. canephora populations, and we investigated associations between these descriptors and forest disturbance and regeneration. Therefore, we sampled 256 C. canephora individuals within 24 plots across three forest categories in Yangambi (DR Congo), and used genotyping-by-sequencing to identify 18,894 SNPs. Overall, we found high genetic diversity, and no evidence of genetic erosion in C. canephora in disturbed old-growth forest, as compared to undisturbed old-growth forest. In addition, an overall heterozygosity excess was found in all populations, which was expected for a self-incompatible species. Genetic structure was mainly a result of isolation-by-distance, reflecting geographical location, with low to moderate relatedness at finer scales. Populations in regrowth forest had lower allelic richness than populations in old-growth forest and were characterised by a lower inter-individual relatedness and a lack of isolation-by-distance, suggesting that they originated from different neighbouring populations and were subject to founder effects. Wild Robusta coffee populations in the study area still harbour high levels of genetic diversity, yet careful monitoring of their response to ongoing forest degradation remains required.

Ecological and genomic vulnerability to climate change across native populations of Robusta coffee (Coffea canephora).

The assessment of population vulnerability under climate change is crucial for planning conservation as well as for ensuring food security. Coffea canephora is, in its native habitat, an understorey tree that is mainly distributed in the lowland rainforests of tropical Africa. Also known as Robusta, its commercial value constitutes a significant revenue for many human populations in tropical countries. Comparing ecological and genomic vulnerabilities within the species' native range can provide valuable insights about habitat loss and the species' adaptive potential, allowing to identify genotypes that may act as a resource for varietal improvement. By applying species distribution models, we assessed ecological vulnerability as the decrease in climatic suitability under future climatic conditions from 492 occurrences. We then quantified genomic vulnerability (or risk of maladaptation) as the allelic composition change required to keep pace with predicted climate change. Genomic vulnerability was estimated from genomic environmental correlations throughout the native range. Suitable habitat was predicted to diminish to half its size by 2050, with populations near coastlines and around the Congo River being the most vulnerable. Whole-genome sequencing revealed 165 candidate SNPs associated with climatic adaptation in C. canephora, which were located in genes involved in plant response to biotic and abiotic stressors. Genomic vulnerability was higher for populations in West Africa and in the region at the border between DRC and Uganda. Despite an overall low correlation between genomic and ecological vulnerability at broad scale, these two components of vulnerability overlap spatially in ways that may become damaging. Genomic vulnerability was estimated to be 23% higher in populations where habitat will be lost in 2050 compared to regions where habitat will remain suitable. These results highlight how ecological and genomic vulnerabilities are relevant when planning on how to cope with climate change regarding an economically important species.

Development and evaluation of a genome-wide Coffee 8.5K SNP array and its application for high-density genetic mapping and for investigating the origin of Coffea arabica L.

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.