Establishing the genetic diversity and population structure of a species can guide the selection of appropriate conservation and sustainable utilization strategies. Next-generation sequencing (NGS) approaches are increasingly being used to generate multi-locus data for genetic structure determination. This study presents the genetic structure of a fodder species -Trema orientalis based on two genome-wide high-throughput diversity array technology (DArT) markers; silicoDArT and single nucleotide polymorphisms (SNPs). Genotyping of 119 individuals generated 40,650 silicoDArT and 4767 SNP markers. Both marker types had a high average scoring reproducibility (>99%). Genetic relationships explored by principal coordinates analysis (PCoA) showed that the first principal coordinate axis explained most of the variation in both the SilicoDArT (34.2%) and SNP (89.6%) marker data. The average polymorphic information content did not highly differ between silicoDArT (0.22) and SNPs (0.17) suggesting minimal differences in informativeness in the two groups of markers. The, mean observed (Ho) and expected (He) heterozygosity were low and differed between the silicoDArT and SNPs respectively, estimated at Ho = 0.08 and He = 0.05 for silicoDArT and Ho = 0.23 and He = 0.19 for SNPs. The population of T. orientalis was moderately differentiated (FST  =  0.20–0.53) and formed 2 distinct clusters based on maximum likelihood and principal coordinates analysis. Analysis of molecular variance revealed that clusters contributed more to the variation (46.3–60.8%) than individuals (32.9–31.2%). Overall, the results suggest a high relatedness of the individuals sampled and a threatened genetic potential of T. orientalis in the wild. Therefore, genetic management activities such as ex-situ germplasm management are required for the sustainability of the species. Ex-situ conservation efforts should involve core collection of individuals from different populations to capture efficient diversity. This study demonstrates the importance of silicoDArT and SNP makers in population structure and genetic diversity analysis of Trema orientalis, useful for future genome wide studies in the species.

ObjectiveThe objective of the study was to investigate the relative abundance and effect of post-harvest treatment on total phenolics (TP) and total alkaloids in the leaves and bark of Carissa edulis and Zanthoxylum chalybeum, which would give an indication of the suitability of leaves as alternative sources of medicine in these plant species.ResultsResults indicated higher levels of total phenolics than total alkaloids in both of the species under both freezing and air drying conditions. While more alkaloids were found in leaves compared to bark, there was no difference in abundance of phenols between the plant parts of both species. Air drying preserved more TPs than freezing and the opposite was true for alkaloids. For sustainability, leaves are recommended as an alternative source of medicine instead of the preferred root or stem bark. However, the choice of whether to dry or freeze will depend on the specific compound of interest. Assessment of spatial variability of medicinal properties is highly recommended.

The focus of this study was to determine the genomic prediction (GP) algorithms with the highest prediction accuracies for reducing the breeding and selection cycles in <i>Vitellaria paradoxa</i>. The efficiency of the GP algorithms were compared to evaluate five Shea tree growth traits in 708 genotypes with 30734 Single Nucleotide Polymorphic (SNPs) markers, which were reduced to 27063 after removing duplicates. Five hundred forty-nine (77.54%) Shea tree training population and 159 (22.46%) training population were genotyped for 30734 single nucleotide polymorphisms (SNPs) and phenotyped for five Shea tree growth traits. We built a model using phenotype and marker data from a training population by optimizing its genomic prediction accuracy for effectiveness of GS. The phenotype and marker data were used for cross validation of the prediction accuracies of the different models. Prediction accuracies varied among the genomic prediction algorithms based on the five phenotypic traits. We determined the best genomic algorithm that is more suitable for reduction of selection and breeding cycles in <i>Vitellaria paradoxa</i>. The GP algorithms were evaluated and we conclude that rrBLUP is the best for improving the prediction accuracy for reducing the breeding cycle in Shea tree.

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The cowpea aphid (Aphis craccivora Koch) is an economically important pest, whose feeding effects cause stunting, delayed flower initiation and yield reduction in cowpea (Vigna unguiculata L. Walp). Host plant resistance offers an alternative for controlling aphids; while simultaneously reducing reliance on chemical pesticides. The objective of this study was to evaluate a multi-parent advanced generation inter-cross (MAGIC) population of cowpea against aphids, across cowpea growing regions in Uganda. The study was arranged in alpha lattice design, with two replicates in three locations over two seasons (2018B and 2019A). Results revealed significant effects (P<0.001) for the main treatment effects, genotype x location and location x season interaction for both infestation and damage. The genotype x season interaction was significant (P<0.01) for both aphid infestation and damage; while the three-way interaction was only significant (P<0.001) for aphid infestation, but not for damage. The study identified five new resistant and stable genotypes from the MAGIC panel, including MAGIC131, MAGIC-132, MAGIC149, MAGIC170 and MAGIC280; and one resistant parent, SUVITA-2. The study further revealed MAGIC-125, MAGIC-171, MAGIC153, MAGIC-333, MAGIC177, MAGIC-292, MAGIC282, MAGIC249, MAGIC162, SEC 4W * SEC 5T, NAROCOWPEA 4, MAGIC-204, MAGIC-039, MAGIC060, MAGIC-097, NAROCOWPEA 3, MAGIC-233, MAGIC090 and MU 9 to be moderately resistant and high yielding genotypes. The above genotypes are recommended for use in the cowpea breeding programme, to develop improved resistant lines against aphids in Uganda.