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South Eastern Bantu-speaking (SEB) groups constitute more than 80% of the population in South Africa. Despite clear linguistic and geographic diversity, the genetic differences between these groups have not been systematically investigated. Based on genome-wide data of over 5000 individuals, representing eight major SEB groups, we provide strong evidence for fine-scale population structure that broadly aligns with geographic distribution and is also congruent with linguistic phylogeny (separation of Nguni, Sotho-Tswana and Tsonga speakers). Although differential Khoe-San admixture plays a key role, the structure persists after Khoe-San ancestry-masking. The timing of admixture, levels of sex-biased gene flow and population size dynamics also highlight differences in the demographic histories of individual groups. The comparisons with five Iron Age farmer genomes further support genetic continuity over ~400 years in certain regions of the country. Simulated trait genome-wide association studies further show that the observed population structure could have major implications for biomedical genomics research in South Africa., Despite linguistic and geographic diversity in South Eastern Bantu-speaking (SEB) groups of South Africa, genetic variation in these groups has not been investigated in depth. Here, the authors analyse genome-wide data from 5056 individuals, providing insights into demographic history across SEB groups.

Genetic variation and susceptibility to disease are shaped by human demographic history and adaptation. We can now study the genomes of extant Africans and uncover traces of population migration, admixture, assimilation and selection by applying sophisticated computational algorithms. There are four major ethnolinguistic divisions among present day Africans: Hunter-gatherer populations in southern and central Africa; Nilo-Saharan speakers from north and northeast Africa; Afro-Asiatic speakers from north and east Africa; and Niger-Congo speakers who are the predominant ethnolinguistic group spread across most of sub-Saharan Africa. The enormous ethnolinguistic diversity in sub-Saharan African populations is largely paralleled by extensive genetic diversity and until a decade ago, little was known about detailed origins and divergence of these groups. Results from large-scale population genetic studies, and more recently whole genome sequence data, are unravelling the critical role of events like migration and admixture and environmental factors including diet, infectious diseases and climatic conditions in shaping current population diversity. It is now possible to start providing quantitative estimates of divergence times, population size and dynamic processes that have affected populations and their genetic risk for disease. Finally, the availability of ancient genomes from Africa provides historical insights of unprecedented depth. In this review, we highlight some key interpretations that have emerged from recent African genome studies.

This publication hasn't any creative commons license associated. This deposit is composed by the main article plus the supplementary materials of the publication. This deposit is composed by a publication in which the IGC's authors have had the role of collaboration (it's a collaboration publication). This type of deposit in ARCA is in restrictedAccess (it can't be in open access to the public), and can only be accessed by two ways: either by requesting a legal copy from the author (the email contact present in this deposit) or by visiting the following link: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005715#sec022 Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge "Introduction to Bioinformatics" course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery-mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online "question and discussion" forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings. National Human Genome Research Institute; Office of the Director; National Institutes of Health grant: (U41HG006941). info:eu-repo/semantics/publishedVersion

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so., Author summary Many programs have been developed to boost the technical and computational skills of scientists working in low to medium income countries (LMIC), who often struggle to remain competitive with their peers in more developed parts of the world. Typically, these programs rely on intensive workshops where students acquire and exercise these skills under the supervision of experienced trainers. However, when trainees return to their home institutions, even after extensive exposure to state of the art techniques, they often find it difficult to put the skills they have acquired into practice and to establish themselves as fully independent practitioners. We have attempted to build a framework through which teams of scientists in African research groups can demonstrate that they have acquired the necessary skills to analyze different types of genomic datasets. Three teams of scientists who have successfully submitted to this assessment exercise report their positive experiences. Many potential participants have so far declined the opportunity, and we discuss the reasons for their reluctance as well as possible ways to facilitate their engagement and provide them with incentives. We argue that assessments such as this could be part of any program aiming to develop technical skills in scientists wishing to support genomic research programs.

International audience; The application of genomics technologies to medicine and biomedical research is increasing in popularity, made possible by new high-throughput genotyping and sequencing technologies and improved data analysis capabilities. Some of the greatest genetic diversity among humans, animals, plants, and microbiota occurs in Africa, yet genomic research outputs from the continent are limited. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive the development of genomic research for human health in Africa, and through recognition of the critical role of bioinformatics in this process, spurred the establishment of H3ABioNet, a pan-African bioinformatics network for H3Africa. The limitations in bioinformatics capacity on the continent have been a major contributory factor to the lack of notable outputs in high-throughput biology research. Although pockets of high-quality bioinformatics teams have existed previously, the majority of research institutions lack experienced faculty who can train and supervise bioinformatics students. H3ABioNet aims to address this dire need, specifically in the area of human genetics and genomics, but knock-on effects are ensuring this extends to other areas of bioinformatics. Here, we describe the emergence of genomics research and the development of bioinformatics in Africa through H3ABioNet.

Background Pseudoxanthoma elasticum (PXE) is an autosomal recessive metabolic disorder with ectopic mineralization in the skin, eyes and cardiovascular system. PXE is caused by mutations in ABCC6 . Objective To examine 54 unrelated South African PXE patients for ABCC6 PXE causing mutations. Methods Patients were screened for mutations in ABCC6 using two strategies. The first involved a comprehensive screening of all the ABCC6 exons and flanking regions by dHPLC or sequencing whereas the second involved screening patients only for the common PXE mutations. The ABCC6 gene was screened in ten white and ten black healthy unrelated South Africans in order to examine the level of common non-PXE associated variation. Results The Afrikaner founder mutation, R1339C, was present in 0.41 of white ABCC6 PXE alleles, confirming the founder effect and its presence in both Afrikaans- (34/63 PXE alleles) and English-speakers (4/28). Eleven mutations were detected in the white patients (of European origin), including two nonsense mutations, 6 missense mutations, two frameshift mutations and a large deletion mutation. The five "Coloured" patients (of mixed Khoisan, Malay, European and African origin) included three compound heterozygotes with R1339C as one of the mutations. The three black patients (sub-Saharan African origin) were all apparent homozygotes for the R1314W mutation. Blacks showed a trend towards a higher degree of neurtral variation (18 variants) when compared to whites (12 variants). Conclusion Delineation of the ABCC6 mutation profile in South African PXE patients will be used as a guide for molecular genetic testing in a clinical setting and for genetic counselling.

Background Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data. Results The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones. Conclusions Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Keratolytic winter erythema (KWE), also known as Oudtshoorn skin disease, is characterised by a cyclical disruption of normal epidermal keratinisation affecting primarily the palmoplantar skin with peeling of the palms and soles, which is worse in the winter. It is a rare monogenic, autosomal dominant condition of unknown cause. However, due to a founder effect, it occurs at a prevalence of 1/7 200 among South African Afrikaans-speakers. In the mid-1980s, samples were collected from affected families for a linkage study to pinpoint the location of the KWE gene. A genome-wide linkage analysis, using microsatellite markers, identified the KWE critical region on chromosome 8p23.1-p22. Subsequent genetic studies focused on screening candidate genes in this critical region; however, no pathogenic mutations that segregated exclusively with KWE were identified. The cathepsin B (CTSB) and farnesyl-diphosphate farnesyltransferase 1 (FDFT1) genes revealed no potentially pathogenic variants, nor did they show differential gene expression in affected skin. Mutation detection in additional candidate genes also failed to identify the KWE-associated variant, suggesting that the causal variant may be in an uncharacterised functional region. Bioinformatic analysis revealed highly conserved regions within the KWE critical region and a custom tiling array was designed to cover this region and to search for copy number variation. Although the study did not identify a variant that segregates exclusively with KWE, it provided valuable insight into the complex KWE-linked region. Next-generation sequencing approaches are being used to comb the region, but the causal variant for this interesting hyperkeratotic palmoplantar phenotype still remains elusive.

FOXP2 is a member of the P subfamily of FOX transcription factors, the DNA-binding domain of which is the winged helix forkhead domain (FHD). In this work we show that the FOXP2 FHD is able to bind to various DNA sequences, including a novel sequence identified in this work, with different affinities and rates as detected using surface plasmon resonance. Combining the experimental work with molecular docking, we show that high-affinity sequences remain bound to the protein for longer, form a greater number of interactions with the protein and induce a greater structural change in the protein than low-affinity sequences. We propose a binding model for the FOXP2 FHD that involves three types of binding sequence: low affinity sites which allow for rapid scanning of the genome by the protein in a partially unstructured state; moderate affinity sites which serve to locate the protein near target sites and high-affinity sites which secure the protein to the DNA and induce a conformational change necessary for functional binding and the possible initiation of downstream transcriptional events.