Genetic architecture reflects the pattern of effects and interaction of genes underlying phenotypic variation. Most mapping and breeding approaches generally consider the additive part of variation but offer limited knowledge on the benefits of epistasis which explains in part the variation observed in traits. In this study, the cowpea multiparent advanced generation inter-cross (MAGIC) population was used to characterize the epistatic genetic architecture of flowering time, maturity, and seed size. In addition, consideration for epistatic genetic architecture in genomic-enabled breeding (GEB) was investigated using parametric, semi-parametric, and non-parametric genomic selection (GS) models. Our results showed that large and moderate effect–sized two-way epistatic interactions underlie the traits examined. Flowering time QTL colocalized with cowpea putative orthologs of Arabidopsis thaliana and Glycine max genes like PHYTOCLOCK1 (PCL1 [Vigun11g157600]) and PHYTOCHROME A (PHY A [Vigun01g205500]). Flowering time adaptation to long and short photoperiod was found to be controlled by distinct and common main and epistatic loci. Parametric and semi-parametric GS models outperformed non-parametric GS model, while using known quantitative trait nucleotide(s) (QTNs) as fixed effects improved prediction accuracy when traits were controlled by large effect loci. In general, our study demonstrated that prior understanding of the genetic architecture of a trait can help make informed decisions in GEB.

Coffea stenophylla is a rare Coffea species boasting a flavor profile comparable to Arabica coffee (Coffea arabica) and has a good adaptability to lowland tropical climates. This species faces increasing threats from climate change, deforestation, and habitat fragmentation in its West African homeland. Using 1037 novel SNP markers derived from Genotyping-by-Sequencing (GBS), we revealed the presence of three distinct natural populations (mean Fst = 0.176) in Sierra Leone. Evidence of recent bottlenecks and small effective population size (118–140) was found across all three populations, reflecting the impact of recent anthropogenic disturbances on this species. Using a model-flexible inference approach, we unveiled a strong ancient bottleneck approximately 23,000 years ago, coinciding with the last glacial maximum (LGM), followed by post-glacial expansion and divergence into distinct genetic clusters. A comparative analysis between ex situ genebanks and natural populations detected a significant gap in genetic diversity, with two out of three natural populations missing from the ex situ genebank collection. These findings highlight the urgent need to improve conservation practices for C. stenophylla in Sierra Leone. The novel SNP markers developed in this study provided valuable tools to support future efforts in conservation and utilization of C. stenophylla genetic resources in West Africa.

Coffee is a major cash and export crops in Sierra Leone and is mainly cultivated in southern and eastern provinces. Kenema, Kailahun, Moyamba, Bo, Pujehun and Kono are major coffee growing districts in the country. This study looks at the extent of phenotypic diversity of the rare and wild Coffea stenophylla in Kenema and Moyamba districts. The Shannon-Weaver diversity were computed for the 13 qualitative parameters of the International Plant Genetic Resources Institute. The Shannon-Weaver diversity revealed variations among the samples for the observed 13 morphological traits which ranges from (H'=0) for both fruit colour and calyx limb persistence to (H'=0.87) for angle of insertion of primary branches on the main stem. Among the 13 qualitative traits assessed, angle of insertion of primary branches on main stem (H' = 0.87), growth habit (H' = 0.78), bean size (H' = 0.75), young leaf colour (H' = 0.66), stem habit (H' = 0.66) and fruit shape (H' = 0.65) exhibited high level of diversity while seed shape (H' = 0.58), stipule shape (H' = 0.46), leaf shape (H' = 0.43), seed uniformity (H' = 0.31) and leaf apex shape (H' = 0.06) showed low level of diversity. This is the first report of phenotypic diversity of Coffea stenophylla in Sierra Leone and the study thus unraveled existence of diversity among samples. It is recommended that these observed variabilities be exploited in order to develop better accessions that are high yielding yet maintaining the same taste. Additionally, genetic fingerprinting need to be applied to provide a complementary assessment of the observed phenotypic diversity.

Genetic architecture reflects the pattern of effects and interaction of genes underling phenotypic variation. Most mapping and breeding approaches generally consider the additive part of variation but offer limited knowledge on the benefits of epistasis which explains in part the variation observed in traits. In this study, the cowpea multiparent advanced generation inter-cross (MAGIC) population was used to characterize the epistatic genetic architecture of flowering time, maturity, and seed size. In addition, considerations for epistatic genetic architecture in genomic-enabled breeding (GEB) was investigated using parametric, semi-parametric, and non-parametric genomic selection (GS) models. Our results showed that large and moderate effect sized two-way epistatic interactions underlie the traits examined. Flowering time QTL colocalized with cowpea putative orthologs of Arabidopsis thaliana and Glycine max genes like PHYTOCLOCK1 ( PCL1 [Vigun11g157600]) and PHYTOCHROME A ( PHY A [Vigun01g205500]). Flowering time adaptation to long and short photoperiod was found to be controlled by distinct and common main and epistatic loci. Parametric and semi-parametric GS models outperformed non-parametric GS model. Using known QTL as fixed effects in GS models improved prediction accuracy when traits were controlled by both large and moderate effect QTL. In general, our study demonstrated that prior understanding the genetic architecture of a trait can help make informed decisions in GEB. This is the first report to characterize epistasis and provide insights into the underpinnings of GS versus marker assisted selection in cowpea.