ArticleBMC plant biology2026
Uncovering the historic genetic diversity of Ugandan Robusta coffee germplasm: a foundation for core collection design.
Article in BMC plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
backgroundUganda is a primary centre of diversity for Coffea canephora (Robusta coffee), a crop that underpins both the national coffee sector and global breeding programs. The National Coffee Research Institute (NaCORI) of Uganda conserves more than 2058 accessions that were collected from different agroecological zones of the country. However, their genetic diversity has been only partly characterized, limiting their effective use in conservation and breeding.
resultsA total of 909 C. canephora accessions from the NaCORI collection was genotyped, using 236 KASPar SNP markers. To investigate genetic structure and diversity we combined multivariate analyses, genetic diversity and differentiation metrics as well as hierarchical clustering. Genetic clusters were then spatially mapped according to the agroecological regions of origin across Uganda. Using reference genotypes from known wild Ugandan forests and major African genetic groups we observed that accessions from NaCORI were majorly related to the genetic group O from Uganda (and to a lesser extent Congolese group E). Despite the low differentiation among regional subpopulations of origin, reflecting gene flow driven by historical dissemination and admixture within the collection, the cultivated accessions were separated into six distinct clusters using Ward's hierarchical method. From these genetic clusters, two core collections were designed using Core Hunter 3. The first comprised 109 accessions with high allelic coverage (CV = 0.981), while the second comprised 328 accessions that, in addition to allelic coverage, optimized the representation of both geographical origin and genetic clusters. These corresponded to 13% and 42% of the entire studied collection, respectively. The core collection of 328 accessions was defined as the GWAS population for downstream association studies. Including representative wild Ugandan accessions in the analyses reveals that some forests may harbour unique diversity absent from the cultivated germplasm.
conclusionCharacterizing this diversity and designing representative core and GWAS collections are essential to optimize resource management and enable the targeted development of climate-resilient cultivars. The multi-regional origin of our core collections revealed the influence of ecological and socio-cultural factors on germplasm diversity. Our results also suggest that including wild accessions from Ugandan forests could greatly enhance the cultivated genetic pool.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.