Human OMICs and Computational Biology Research in Africa: Current Challenges and Prospects

Abstract

Following the publication of the first human genome, OMICs research, including genomics, transcriptomics, proteomics, and metagenomics, has been on the rise. OMICs studies revealed the complex genetic diversity among human populations and challenged our understandings of genotype-phenotype correlations. Africa, being the cradle of the first modern humans, is distinguished by a large genetic diversity within its populations and rich ethnolinguistic history. However, the available human OMICs tools and databases are not representative of this diversity, therefore creating significant gaps in biomedical research. African scientists, students, and publics are among the key contributors to OMICs systems science. This expert review examines the pressing issues in human OMICs research, education, and development in Africa, as seen through a lens of computational biology, public health relevant technology innovation, critically-informed science governance, and how best to harness OMICs data to benefit health and societies in Africa and beyond. We underscore the disparities between North and Sub-Saharan Africa at different levels. A harmonized African ethnolinguistic classification would help address annotation challenges associated with population diversity. Finally, building on the existing strategic research initiatives, such as the H3Africa and H3ABioNet Consortia, we highly recommend addressing large-scale multidisciplinary research challenges, strengthening research collaborations and knowledge transfer, and enhancing the ability of African researchers to influence and shape national and international research, policy, and funding agendas. This article and analysis contribute to a deeper understanding of past and current challenges in the African OMICs innovation ecosystem, while also offering foresight on future innovation trajectories.

Two Decades of Desiccation Biology: A Systematic Review of the Best Studied Angiosperm Resurrection Plants

“…A number of the resurrection plants native to the Global South were studied in European countries without instigating collaboration. This could be attributed to the narrow distribution of resurrection plants in the Global North as well as differences in funding and resources available for research in the Global North relative to the Global South [70]. Despite these imbalances, South Africa remains a leader in the research of angiosperm resurrection plants.…”

“…These patterns further reinforce the notion that economic barriers limit participation in omics studies by teams working exclusively in the Global South. Omics research is underrepresented in Africa, not only in plant biology, but also in the biomedical research [70] and these challenges are mainly associated with socio-economic factors. In this regard, we urge researchers to develop more collaborations between countries with a rich diversity of desiccation tolerant plants and countries with economic resources.…”

The Development of a Sustainable Bioinformatics Training Environment Within the H3Africa Bioinformatics Network (H3ABioNet)

“…Data modellers gained a much better understanding and appreciation of why biological data can inherently be noisy, while data generators gained more knowledge of statistical modelling and analysis methods for their data (Ghouila et al, 2018). Apart from peer learning and knowledge transfer, hackathons are a great way of improving communication, fostering long term cohesion and collaboration between scientists and engineers while working towards common goals, as in the case of the H3ABioNet hackathon for the development of a genomic medicine and microbiome portal for African genomics data (Radouani et al, 2020;Fadlelmola et al, 2021;Hamdi et al, 2021).…”

African Genomic Medicine Portal: A Web Portal for Biomedical Applications

“…Current genomics and biomedical data and metadata in public databases are skewed toward populations of European ancestry. Many African populations remain underrepresented and the data that is available for Africa is not structured in a manner appropriate for the geographical, social and cultural diversity of the continent, with data generally being classified under Sub-Saharan Africa, with little reference to specific populations, or misclassified with other regional groups, as previously described [2,3]. Recent advances in genomics have illustrated the rich genetic diversity of African populations [4,5] and its associated health implications, such as varying lipid profiles [6], predisposition to kidney disease [7] and more [8].…”