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.

Genome Scan for Variable Genes Involved in Environmental Adaptations of Nubian Ibex.

The Nubian ibex (Capra nubiana) is a wild goat species that inhabits the Sahara and Arabian deserts and is adapted to extreme ambient temperatures, intense solar radiation, and scarcity of food and water resources. To investigate desert adaptation, we explored the possible role of copy number variations (CNVs) in the evolution of Capra species with a specific focus on the environment of Capra nubiana. CNVs are structural genomic variations that have been implicated in phenotypic differences between species and could play a role in species adaptation. CNVs were inferred from Capra nubiana sequence data relative to the domestic goat reference genome using read-depth approach. We identified 191 CNVs overlapping with protein-coding genes mainly involved in biological processes such as innate immune response, xenobiotic metabolisms, and energy metabolisms. We found copy number variable genes involved in defense response to viral infections (Cluster of Differentiation 48, UL16 binding protein 3, Natural Killer Group 2D ligand 1-like, and Interferon-induced transmembrane protein 3), possibly suggesting their roles in Nubian ibex adaptations to viral infections. Additionally, we found copy number variable xenobiotic metabolism genes (carboxylesterase 1, Cytochrome P450 2D6, Glutathione S-transferase Mu 4, and UDP Glucuronosyltransferase-2B7), which are probably an adaptation of Nubian ibex to desert diets that are rich in plant secondary metabolites. Collectively, this study's results advance our understanding of CNVs and their possible roles in the adaptation of Nubian ibex to its environment. The copy number variable genes identified in Nubian ibex could be considered as subjects for further functional characterizations.

The first complete genome sequence of the African swine fever virus genotype X and serogroup 7 isolated in domestic pigs from the Democratic Republic of Congo.

BACKGROUND: African swine fever (ASF), a highly contagious hemorrhagic disease, affects domestic pigs in the Democratic Republic of Congo (DRC) where regular outbreaks are reported leading to high mortality rates approaching 100% in the affected regions. No study on the characteristics of the complete genome of strains responsible for ASF outbreaks in the South Kivu province of DRC is available, limited a better understanding of molecular evolution and spread of this virus within the country. The present study aimed at determining the complete genome sequence of ASFV strains genotype X involved in 2018-2019 ASF disease outbreaks in South Kivu province of DRC. MATERIALS AND METHODS: Genomic DNA of a spleen sample from an ASFV genotype X-positive domestic pig in Uvira, during the 2018-2019 outbreaks in South Kivu, was sequenced using the Illumina HiSeq X platform. Obtained trimmed reads using Geneious Prime 2020.0.4 were blasted against a pig reference genome then contigs were generated from the unmapped reads enriched in ASFV DNA using Spades implemented in Geneious 2020.0.4. The assembly of the complete genome sequence of ASFV was achieved from the longest overlapping contigs. The new genome was annotated with the genome annotation transfer utility (GATU) software and the CLC Genomics Workbench 8 software was further used to search for any ORFs that failed to be identified by GATU. Subsequent analyses of the newly determined Uvira ASFV genotype X genome were done using BLAST for databases search, CLUSTAL W for multiple sequences alignments and MEGA X for phylogeny. RESULTS: 42 Gbp paired-end reads of 150 bp long were obtained containing about 0.1% of ASFV DNA. The assembled Uvira ASFV genome, termed Uvira B53, was 180,916 bp long that could be assembled in 2 contigs. The Uvira B53genome had a GC content of 38.5%, encoded 168 open reading frames (ORFs) and had 98.8% nucleotide identity with the reference ASFV genotype X Kenya 1950. The phylogenetic relationship with selected representative genomes clustered the Uvira B53 strain together with ASFV genotype X reported to date (Kenya 1950 and Ken05/Tk1). Multiple genome sequences comparison with the two reference ASFV genotype X strains showed that 130 of the 168 ORFs were fully conserved in the Uvira B53. The other 38 ORFs were divergent mainly due to SNPs and indels (deletions and insertions). Most of 46 multigene family (MGF) genes identified were affected by various genetic variations. However, 8 MGF ORFs present in Kenya 1950 and Ken05/Tk1 were absent from the Uvira B53 genome including three members of MGF 360, four of MGF 110 and one of MGF 100 while one MGF ORF (MGF 360-1L) at the left end of the genome was truncated in Uvira B53. Moreover, ORFs DP96R and p285L were also absent in the Uvira B53 genome. In contrast, the ORF MGF 110-5L present in Uvira B53 and Ken05/Tk1 was missing in Kenya 1950. The analysis of the intergenic region between the I73R and I329L genes also revealed sequence variations between the three genotype X strains mainly characterized by a deletion of 69 bp in Uvira B53 and 36 bp in Kenya 1950, compared to Ken05/Tk1. Assessment of the CD2v (EP402R) antigen unveiled the presence of SNPs and indels particularly in the PPPKPY tandem repeat region between selected variants representing the eight serogroups reported to date. Uvira B53 had identical CD2v variable region to the Uganda (KM609361) strain, the only other ASFV serogroup 7 reported to date. CONCLUSION: We report the first complete genome sequence of an African swine fever virus (ASFV) p72 genotype X and CD2v serogroup 7, termed Uvira B53. This study provides additional insights on genetic characteristics and evolution of ASFV useful for tracing the geographical spread of ASF and essential for improved design of control and management strategies against ASF.

Genome-wide insights of Ethiopian indigenous sheep populations reveal the population structure related to tail morphology and phylogeography.

BACKGROUND: Ethiopian sheep living in different climatic zones and having contrasting morphologies are a most promising subject of molecular-genetic research. Elucidating their genetic diversity and genetic structure is critical for designing appropriate breeding and conservation strategies. OBJECTIVE: The study was aimed to investigate genome-wide genetic diversity and population structure of eight Ethiopian sheep populations. METHODS: A total of 115 blood samples were collected from four Ethiopian sheep populations that include Washera, Farta and Wollo (short fat-tailed) and Horro (long fat-tailed). DNA was extracted using Quick-DNA™ Miniprep plus kit. All DNA samples were genotyped using Ovine 50 K SNP BeadChip. To infer genetic relationships of Ethiopian sheep at national, continental and global levels, genotype data on four Ethiopian sheep (Adilo, Arsi-Bale, Menz and Black Head Somali) and sheep from east, north, and south Africa, Middle East and Asia were included in the study as reference. RESULTS: Mean genetic diversity of Ethiopian sheep populations ranged from 0.352 ± 0.14 for Horro to 0.379 ± 0.14 for Arsi-Bale sheep. Population structure and principal component analyses of the eight Ethiopian indigenous sheep revealed four distinct genetic cluster groups according to their tail phenotype and geographical distribution. The short fat-tailed sheep did not represent one genetic cluster group. Ethiopian fat-rump sheep share a common genetic background with the Kenyan fat-tailed sheep. CONCLUSION: The results of the present study revealed the principal component and population structure follows a clear pattern of tail morphology and phylogeography. There is clear signature of admixture among the study Ethiopian sheep populations.

Hackathons as a means of accelerating scientific discoveries and knowledge transfer.

Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions.

A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without.

BACKGROUND: Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls. METHODS: This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes. RESULTS: Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls. CONCLUSION: Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.

NetCapDB: measuring bioinformatics capacity development in Africa.

BACKGROUND: The National Institutes of Health (USA) has committed 5 years of funding to the Bioinformatics Network of the Human Heredity and Health in Africa initiative. This pan-African network aims to develop capacity for bioinformatics research, in order to provide support to human health genomics research programs ongoing on the continent. Over the 5 years of funding, it is imperative to track changes in bioinformatics capacity at the funded centres and to document how the funding has translated into capacity development during this time frame. RESULTS: The Network capacity database, NetCapDB, is a relational database that captures quantitative metrics for bioinformatics capacity, and tracks the changes in these metrics over time. A graphical user interface allows for straight-forward, browser-based data entry by users across Africa; and for visual and graph-based exploration of captured data. A reporting interface allows for semi-automated generation of standardized reports for monitoring and evaluation purposes.

Sequencing of GJB2 in Cameroonians and Black South Africans and comparison to 1000 Genomes Project Data Support Need to Revise Strategy for Discovery of Nonsyndromic Deafness Genes in Africans.

Mutations in the GJB2 gene, encoding connexin 26, could account for 50% of congenital, nonsyndromic, recessive deafness cases in some Caucasian/Asian populations. There is a scarcity of published data in sub-Saharan Africans. We Sanger sequenced the coding region of the GJB2 gene in 205 Cameroonian and Xhosa South Africans with congenital, nonsyndromic deafness; and performed bioinformatic analysis of variations in the GJB2 gene, incorporating data from the 1000 Genomes Project. Amongst Cameroonian patients, 26.1% were familial. The majority of patients (70%) suffered from sensorineural hearing loss. Ten GJB2 genetic variants were detected by sequencing. A previously reported pathogenic mutation, g.3741_3743delTTC (p.F142del), and a putative pathogenic mutation, g.3816G>A (p.V167M), were identified in single heterozygous samples. Amongst eight the remaining variants, two novel variants, g.3318-41G>A and g.3332G>A, were reported. There were no statistically significant differences in allele frequencies between cases and controls. Principal Components Analyses differentiated between Africans, Asians, and Europeans, but only explained 40% of the variation. The present study is the first to compare African GJB2 sequences with the data from the 1000 Genomes Project and have revealed the low variation between population groups. This finding has emphasized the hypothesis that the prevalence of mutations in GJB2 in nonsyndromic deafness amongst European and Asian populations is due to founder effects arising after these individuals migrated out of Africa, and not to a putative "protective" variant in the genomic structure of GJB2 in Africans. Our results confirm that mutations in GJB2 are not associated with nonsyndromic deafness in Africans.