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Abstract Background The Eastern Africa Network for Bioinformatics Training (EANBiT) has matured through continuous evaluation, feedback, and codesign. We highlight how the program has evolved to meet challenges and achieve its goals and how experiential learning through mini projects enhances the acquisition of skills and collaboration. We continued to learn and grow through honest feedback and evaluation of the program, trainers, and modules, enabling us to provide robust training even during the Coronavirus disease 2019 (COVID-19) pandemic, when we had to redesign the program due to restricted travel and in person group meetings. Results In response to the pandemic, we developed a program to maintain “residential” training experiences and benefits remotely. We had to answer the following questions: What must change to still achieve the RT goals? What optimal platforms should be used? How would we manage connectivity and data challenges? How could we avoid online fatigue? Going virtual presented an opportunity to reflect on the essence and uniqueness of the program and its ability to meet the objective of strengthening bioinformatics skills among the cohorts of students using different delivery approaches. It allowed an increase in the number of participants. Evaluating each program component is critical for improvement, primarily when feedback feeds into the program's continuous amendment. Initially, the participants noted that there were too many modules, insufficient time, and a lack of hands-on training as a result of too much focus on theory. In the subsequent iterations, we reduced the number of modules from 27 to five, created a harmonized repository for the materials on GitHub, and introduced project-based learning through the mini projects. Conclusion We demonstrate that implementing a program design through detailed monitoring and evaluation leads to success, especially when participants who are the best fit for the program are selected on an appropriate level of skills, motivation, and commitment.

Magnaporthe oryzae, a devastating pathogen of finger millet (Eleusine coracana), secretes effector molecules during infection to manipulate host immunity. This study determined the presence of avirulence effector genes PWL1 and PWL2 in 221 Eleusine blast isolates from eastern Africa. Most Ethiopian isolates carried both PWL1 and PWL2. Kenyan and Ugandan isolates largely lacked both genes, and Tanzanian isolates carried either PWL1 or lacked both. The roles of PWL1 and PWL2 towards pathogenicity on alternative chloridoid hosts, including weeping lovegrass (Eragrostis curvula), were also investigated. PWL1 and PWL2 were cloned from Ethiopian isolate E22 and were transformed separately into Ugandan isolate U34, which lacked both genes. Resulting transformants harboring either gene gained varying degrees of avirulence on Eragrostis curvula but remained virulent on finger millet. Strains carrying one or both PWL1 and PWL2 infected the chloridoid species Sporobolus phyllotrichus and Eleusine tristachya, indicating the absence of cognate resistance (R) genes for PWL1 and PWL2 in these species. Other chloridoid grasses, however, were fully resistant, regardless of the presence of one or both PWL1 and PWL2, suggesting the presence of effective R genes against PWL and other effectors. Partial resistance in some Eragrostis curvula accessions to some blast isolates lacking PWL1 and PWL2 also indicated the presence of other interactions between fungal avirulence (AVR) genes and host resistance (R) genes. Related chloridoid species thus harbor resistance genes that could be useful to improve finger millet for blast resistance. Conversely, loss of AVR genes in the fungus could expand its host range, as demonstrated by the susceptibility of Eragrostis curvula to finger millet blast isolates that had lost PWL1 and PWL2. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Abstract Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a ‘poor man’s crop’, finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

Spatial variation and genotype by environment (GxE) interaction are common in varietal selection field trials and pose a significant challenge for plant breeders when comparing the genetic potential of different varieties. Efficient statistical methods must be employed for the evaluation of finger millet breeding trials to accurately select superior varieties that contribute to agricultural productivity. The objective of this study was to improve selection strategies in finger millet breeding in Ethiopia through modeling of spatial field trends and the GxE interaction. A dataset of seven multi-environment trials (MET) conducted in randomized complete block design (RCBD) with two replications laid out in rectangle (row x column) arrays of plots was used in this study. The results revealed that, under the linear mixed model, the spatial and factor analytic (FA) models were efficient methods of data analysis for this study, and this was demonstrated with evidence of heritability measure. We found two clusters of correlated environments that helped to select superior and stable varieties through ranking average Best Linear Unbiased Predictors (BLUPs) within clusters. The first cluster was chosen because it contained a greater number of environments with high heritability. Based on this cluster, Bako-09, 203439, 203325, and 203347 were the top four varieties with relatively high yield performance and stability across correlated environments. Hence, scaling up the use of this efficient analysis method will improve the selection of superior finger millet varieties.

The Human Leukocyte Antigen (HLA) region plays an important role in autoimmune and infectious diseases. HLA is a highly polymorphic region and thus difficult to impute. We, therefore, sought to evaluate HLA imputation accuracy, specifically in a West African population, since they are understudied and are known to harbor high genetic diversity. The study sets were selected from 315 Gambian individuals within the Gambian Genome Variation Project (GGVP) Whole Genome Sequence datasets. Two different arrays, Illumina Omni 2.5 and Human Hereditary and Health in Africa (H3Africa), were assessed for the appropriateness of their markers, and these were used to test several imputation panels and tools. The reference panels were chosen from the 1000 Genomes (1kg-All), 1000 Genomes African (1kg-Afr), 1000 Genomes Gambian (1kg-Gwd), H3Africa, and the HLA Multi-ethnic datasets. HLA-A, HLA-B, and HLA-C alleles were imputed using HIBAG, SNP2HLA, CookHLA, and Minimac4, and concordance rate was used as an assessment metric. The best performing tool was found to be HIBAG, with a concordance rate of 0.84, while the best performing reference panel was the H3Africa panel, with a concordance rate of 0.62. Minimac4 (0.75) was shown to increase HLA-B allele imputation accuracy compared to HIBAG (0.71), SNP2HLA (0.51) and CookHLA (0.17). The H3Africa and Illumina Omni 2.5 array performances were comparable, showing that genotyping arrays have less influence on HLA imputation in West African populations. The findings show that using a larger population-specific reference panel and the HIBAG tool improves the accuracy of HLA imputation in a West African population.

Coral reefs face an increased number of environmental threats from anthropomorphic climate change and pollution from agriculture, industries and sewage. Because environmental changes lead to their compositional and functional shifts, coral reef microbial communities can serve as indicators of ecosystem impacts through development of rapid and inexpensive molecular monitoring tools. Little is known about coral reef microbial communities of the Western Indian Ocean (WIO). We compared taxonomic and functional diversity of microbial communities inhabiting near-coral seawater and sediments from Kenyan reefs exposed to varying impacts of human activities. Over 19,000 species (bacterial, viral and archaeal combined) and 4,500 clusters of orthologous groups of proteins (COGs) were annotated. The coral reefs showed variations in the relative abundances of ecologically significant taxa, especially copiotrophic bacteria and coliphages, corresponding to the magnitude of the neighboring human impacts in the respective sites. Furthermore, the near-coral seawater and sediment metagenomes had an overrepresentation of COGs for functions related to adaptation to diverse environments. Malindi and Mombasa marine parks, the coral reef sites closest to densely populated settlements were significantly enriched with genes for functions suggestive of mitigation of environment perturbations including the capacity to reduce intracellular levels of environmental contaminants and repair of DNA damage. Our study is the first metagenomic assessment of WIO coral reef microbial diversity which provides a much-needed baseline for the region, and points to a potential area for future research toward establishing indicators of environmental perturbations.

Marine biodiversity is under increasing threat as the area covered by corals diminishes under pressure from climate change and human activities, most of which lead to marine pollution. In Kenya, marine protected areas (MPAs) are the key strategy used to protect coral reefs and biodiversity. However, MPAs' effectiveness to prevent pollution of the reefs has not been specifically assessed. We determined if the levels of surrogates of human-source pollution, i.e., E. coli and nutrient concentrations on Kenyan coral reefs, varied with increasing levels of marine protection at the Kilifi creek (least protection), Malindi Reserve (moderate protection), and Kuruwitu Conservancy (strictest protection). The most probable number (MPN) of E. coli was estimated by serial dilution while nitrate and orthophosphate concentrations were determined spectrophotometrically. As protection increased from “least,” to “moderate” and “strictest,” E. coli concentrations (MPN/100 mL) decreased from 29, to 16 and undetectable, while mean orthophosphate concentrations increased from 0.326, to 0.422 and 0.524 mg/L, respectively. Mean nitrate concentrations, on the other hand, showed no trend with protection. These results suggest the potential of marine protection to mitigate coral reef pollution, especially from microbes. They also point to the possibility that multiple sources of pollution exist on which marine protection may have little or no effect. Significantly, this pilot study points to the need for improved study design to definitively determine the role MPAs may play in protecting against pollution.

Background: Pigeonpea (Cajanus cajan (L.) Millsp.) is a drought tolerant legume of the Fabaceae family and the only cultivated species in the genus Cajanus. It is mainly cultivated in the semi-arid tropics of Asia and Oceania, Africa and America. In Malawi, it is grown as a source of food and income and for soil improvement in intercropping systems. However, varietal contamination due to natural outcrossing causes significant quality reduction and yield losses. In this study, 48 polymorphic SSR markers were used to assess the diversity among all pigeonpea varieties cultivated in Malawi to determine if a genetic fingerprint could be identified to distinguish the popular varieties. Results: A total of 212 alleles were observed with an average of 5.58 alleles per marker and a maximum of 14 alleles produced by CCttc019 (Marker 40). Polymorphic information content (PIC), ranged from 0.03 to 0.89 with an average of 0.30. A neighbor-joining tree produced 4 clusters. The most commonly cultivated varieties, which include released varieties and cultivated land races, were well-spread across all the clusters observed, indicating that they generally represented the genetic diversity available in Malawi, although substantial variation was evident that can still be exploited through further breeding. Conclusion: Screening of the allelic data associated with the five most popular cultivated varieties, revealed 6 markers – CCB1, CCB7, Ccac035, CCttc003, Ccac026 and CCttc019 – which displayed unique allelic profiles for each of the five varieties. This genetic fingerprint can potentially be applied for seed certification to confirm the genetic purity of seeds that are delivered to Malawi farmers.

Abstract  The potential gene flow between a crop and its wild relatives is largely determined by the overlaps in their ecological and geographical distributions. Ecogeographical databases are therefore indispensable tools for the sustainable management of genetic resources. In order to expand our knowledge of Sorghum bicolor distribution in Kenya, we conducted in situ collections of wild, weedy and cultivated sorghum. Qualitative and quantitative morphological traits were measured for each sampled wild sorghum plant. Farmers’ knowledge relating to the management of sorghum varieties and autecology of wild sorghum was also obtained. Cluster analysis supports the existence of several wild sorghum morphotypes that might correspond to at least three of the five ecotypes recognized in Africa. Intermediate forms between wild and cultivated sorghum belonging to the S. bicolor ssp. drummondii are frequently found in predominantly sorghum growing areas. Crop-wild gene flow in sorghum is likely to occur in many agroecosystems of Kenya. [ABSTRACT FROM AUTHOR]