Designing and delivering bioinformatics project-based learning in East Africa.

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.

Assessing HLA imputation accuracy in a West African population.

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.

Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet.

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.

Host Specificity Controlled by PWL1 and PWL2 Effector Genes in the Finger Millet Blast Pathogen Magnaporthe oryzae in Eastern Africa.

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. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Evaluation of finger millet (Eleusine coracana (L.) Gaertn.) in multi-environment trials using enhanced statistical models.

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.

Assessing HLA imputation accuracy in a West African population.

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 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 dataset (1kg-All), 1000 Genomes African dataset (1kg-Afr), 1000 Genomes Gambian dataset (1kg-Gwd), H3Africa dataset and the HLA Multi-ethnic dataset. 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. Overall, 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 West African populations. Author Summary: For studies that associate a particular HLA type to a phenotypic trait for instance HIV susceptibility or control, genotype imputation remains the main method for acquiring a larger sample size. Genotype imputation, process of inferring unobserved genotypes, is a statistical technique and thus deals with probabilities. Also, the HLA region is highly variable and therefore difficult to impute. In view of this, it is important to assess HLA imputation accuracy especially in African populations. This is because the African genome has high diversity, and such studies have hardly been conducted in African populations. This work highlights that using HIBAG imputation tool and a larger population-specific reference panel increases HLA imputation accuracy in an African population.

Cross-Sectional Variations in Structure and Function of Coral Reef Microbiome With Local Anthropogenic Impacts on the Kenyan Coast of the Indian Ocean.

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.

Infestation mechanisms of two woodborer species in the mangrove Sonneratia alba J. Smith in Kenya and co-occurring endophytic fungi.

Insect damage on trees can severely affect the quality of timber, reduce the fecundity of the host and render it susceptible to fungal infestation and disease. Such pathology weakens or eventually kills the host. Infestation by two insect woodborer species (a moth and a beetle) is causing mortality of Sonneratia alba, a wide-ranging pioneer mangrove species of the Indo-Pacific. Establishing the infestation mechanism of the two insect woodborer species is an initial and essential step towards understanding their ecological role in the mangroves and in determining sustainable management priorities and options. Our main objectives were to investigate the infestation mechanism employed by the two insect woodborers which infest S. alba trees, to establish the occurrence of secondary infestation by endophytic fungi in the infested S. alba branches, and to explore a control management option to the woodborer infestation. We conducted an external inspection of infested branches in two large embayments in Kenya, Gazi Bay and Mida Creek, and by splitting infested branches we determined the respective internal infestation mechanisms. Infested wood samples from Gazi Bay and Mida Creek were incubated at 28±1°C for 3-5 days to establish the presence of fungi. A survey was conducted in both Gazi Bay and Mida Creek to ascertain the presence of ants on S. alba. The infestation characteristics of the two insect woodborer species were different. It took 6-8 months for the beetle to kill a branch of 150 cm-200 cm long. For the moth to kill a branch, it depended upon several factors including the contribution by multiple species, other than the moth infestation alone. A total of 15 endophytic fungal species were identified. Two ant species Oecophylla longipoda and a Pheidole sp. inhabited 62% and 69% respectively of sampled S. alba trees in Gazi Bay whereas only Pheidole sp. inhabited 17% of the sampled S. alba trees in Mida Creek. In summary, we have documented the time it takes each woodborer species to kill a branch, the infestation mechanism of the two insect woodborers, and we hypothesized on the role of two ant species. The presence of several different fungal species was ascertained, and we discussed their possible role in the infested wood. Our results cannot unambiguously associate the woodborers and identified fungi. We recommend further studies to investigate the presence or absence, and if present, the nature of fungi in the gut of the woodborers.

Identification of SNP and SSR Markers in Finger Millet Using Next Generation Sequencing Technologies.

Finger millet is an important cereal crop in eastern Africa and southern India with excellent grain storage quality and unique ability to thrive in extreme environmental conditions. Since negligible attention has been paid to improving this crop to date, the current study used Next Generation Sequencing (NGS) technologies to develop both Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP) markers. Genomic DNA from cultivated finger millet genotypes KNE755 and KNE796 was sequenced using both Roche 454 and Illumina technologies. Non-organelle sequencing reads were assembled into 207 Mbp representing approximately 13% of the finger millet genome. We identified 10,327 SSRs and 23,285 non-homeologous SNPs and tested 101 of each for polymorphism across a diverse set of wild and cultivated finger millet germplasm. For the 49 polymorphic SSRs, the mean polymorphism information content (PIC) was 0.42, ranging from 0.16 to 0.77. We also validated 92 SNP markers, 80 of which were polymorphic with a mean PIC of 0.29 across 30 wild and 59 cultivated accessions. Seventy-six of the 80 SNPs were polymorphic across 30 wild germplasm with a mean PIC of 0.30 while only 22 of the SNP markers showed polymorphism among the 59 cultivated accessions with an average PIC value of 0.15. Genetic diversity analysis using the polymorphic SNP markers revealed two major clusters; one of wild and another of cultivated accessions. Detailed STRUCTURE analysis confirmed this grouping pattern and further revealed 2 sub-populations within wild E. coracana subsp. africana. Both STRUCTURE and genetic diversity analysis assisted with the correct identification of the new germplasm collections. These polymorphic SSR and SNP markers are a significant addition to the existing 82 published SSRs, especially with regard to the previously reported low polymorphism levels in finger millet. Our results also reveal an unexploited finger millet genetic resource that can be included in the regional breeding programs in order to efficiently optimize productivity.

SSR genetic diversity assessment of popular pigeonpea varieties in Malawi reveals unique fingerprints

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.

Identification of groundnut (Arachis hypogaea) SSR markers suitable for multiple resistance traits QTL mapping in African germplasm

Background This study aimed to identify and select informative Simple Sequence Repeat (SSR) markers that may be linked to resistance to important groundnut diseases such as Early Leaf Spot, Groundnut Rosette Disease, rust and aflatoxin contamination. To this end, 799 markers were screened across 16 farmer preferred and other cultivated African groundnut varieties that are routinely used in groundnut improvement, some with known resistance traits. Results The SSR markers amplified 817 loci and were graded on a scale of 1 to 4 according to successful amplification and ease of scoring of amplified alleles. Of these, 376 markers exhibited Polymorphic Information Content (PIC) values ranging from 0.06 to 0.86, with 1476 alleles detected at an average of 3.7 alleles per locus. The remaining 423 markers were either monomorphic or did not work well. The best performing polymorphic markers were subsequently used to construct a dissimilarity matrix that indicated the relatedness of the varieties in order to aid selection of appropriately diverse parents for groundnut improvement. The closest related varieties were MGV5 and ICGV-SM 90704 and most distant were Chalimbana and 47-10. The mean dissimilarity value was 0.51, ranging from 0.34 to 0.66. Discussion Of the 376 informative markers identified in this study, 139 (37%) have previously been mapped to the Arachis genome and can now be employed in Quantitative Trait Loci (QTL) mapping and the additional 237 markers identified can be used to improve the efficiency of introgression of resistance to multiple important biotic constraints into farmer-preferred varieties of Sub-Saharan Africa.

Compilation of an informative microsatellite set for genetic characterisation of East African finger millet (Eleusine coracana)

Background Genetic diversity of finger millet (Eleusine coracana), a nutritious neglected staple cereal in Africa and South Asia is largely uncharacterized. This study analysed 82 published SSR markers for finger millet across 10 diverse accessions to compile an informative set for genetic characterisation. Extensive optimization compared single samples with bulked leaf or bulked DNA samples for capturing within accession genetic diversity. The markers were evaluated to determine (1) how efficiently they amplified target loci during high-throughput genotyping with a generic PCR protocol, (2) ease of scoring PCR products and (3) polymorphism and ability to discern genetic diversity within the tested finger millet germplasm. Results Across 88 samples, the 52 markers that worked well amplified 274 alleles, ranging from 2 to 14 per locus with a mean of 4.89. Major allele frequency ranged from 0.18 to 0.93 with a mean of 0.57. Polymorphic Information Content (PIC) ranged from 0.13 to 0.88 with a mean of 0.5 and availability varied between 64 and 100% with a mean of 92.8%. Heterozygosity ranged from 0 to 1.0, with a mean of 0.26. Discussion Five individual samples from an accession captured the largest number of alleles per locus compared to the four different bulked sampling strategies but this difference was not significant. The identified set comprised 20 markers: UGEP24, UGEP53, UGEP84, UGEP27, UGEP98, UGEP95, UGEP64, UGEP33, UGEP67, UGEP106, UGEP110, UGEP57, UGEP96, UGEP66, UGEP46, UGEP79, UGEP20, UGEP12, UGEP73 and UGEP5 and was since used to assess East African finger millet genetic diversity in two separate studies.

Genetic structure and diversity of wild sorghum populations (Sorghum spp.) from different eco-geographical regions of Kenya.

Wild sorghums are extremely diverse phenotypically, genetically and geographically. However, there is an apparent lack of knowledge on the genetic structure and diversity of wild sorghum populations within and between various eco-geographical regions. This is a major obstacle to both their effective conservation and potential use in breeding programs. The objective of this study was to assess the genetic diversity and structure of wild sorghum populations across a range of eco-geographical conditions in Kenya. Sixty-two wild sorghum populations collected from the 4 main sorghum growing regions in Kenya were genotyped using 18 simple sequence repeat markers. The study showed that wild sorghum is highly variable with the Coast region displaying the highest diversity. Analysis of molecular variance showed a significant variance component within and among wild sorghum populations within regions. The genetic structure of wild sorghum populations indicated that gene flow is not restricted to populations within the same geographic region. A weak regional differentiation was found among populations, reflecting human intervention in shaping wild sorghum genetic structure through seed-mediated gene flow. The sympatric occurrence of wild and cultivated sorghums coupled with extensive seed-mediated gene flow, suggests a potential crop-to-wild gene flow and vice versa across the regions. Wild sorghum displayed a mixed mating system. The wide range of estimated outcrossing rates indicate that some environmental conditions may exist where self-fertilisation is favoured while others cross-pollination is more advantageous.

Wild sorghum from different eco-geographic regions of Kenya display a mixed mating system.

Knowledge of mating systems is required in order to understand the genetic composition and evolutionary potential of plant populations. Outcrossing in a population may co-vary with the ecological and historical factors influencing it. However, literature on the outcrossing rate is limited in terms of wild sorghum species coverage and eco-geographic reference. This study investigated the outcrossing rates in wild sorghum populations from different ecological conditions of Kenya. Twelve wild sorghum populations were collected in four sorghum growing regions. Twenty-four individuals per population were genotyped using six polymorphic simple sequence repeat (SSR) markers to compute their indirect equilibrium estimates of outcrossing rate as well as population structure. In addition, the 12 populations were planted in a field in a randomised block design with five replications. Their progeny (250 individuals per population) were genotyped with the six SSR markers to estimate multi-locus outcrossing rates. Equilibrium estimates of outcrossing rates ranged from 7.0 to 75.0%, while multi-locus outcrossing rates (t (m)) ranged from 8.9 to 70.0% with a mean of 49.7%, indicating that wild sorghum exhibits a mixed mating system. The wide range of estimated outcrossing rates in wild sorghum populations indicate that environmental conditions may exist under which fitness is favoured by outcrossing and others under which selfing is more advantageous. The genetic structure of the populations studied is concordant with that expected for a species displaying mixed mating system.