African evolutionary history inferred from whole genome sequence data of 44 indigenous African populations

Deep history of cultural and linguistic evolution among Central African hunter-gatherers

Human evolutionary history in Central Africa reflects a deep history of population connectivity. However, Central African hunter-gatherers (CAHGs) currently speak languages acquired from their neighbouring farmers. Hence it remains unclear which aspects of CAHG cultural diversity results from long-term evolution preceding agriculture and which reflect borrowing from farmers. On the basis of musical instruments, foraging tools, specialized vocabulary and genome-wide data from ten CAHG populations, we reveal evidence of large-scale cultural interconnectivity among CAHGs before and after the Bantu expansion. We also show that the distribution of hunter-gatherer musical instruments correlates with the oldest genomic segments in our sample predating farming. Music-related words are widely shared between western and eastern groups and likely precede the borrowing of Bantu languages. In contrast, subsistence tools are less frequently exchanged and may result from adaptation to local ecologies. We conclude that CAHG material culture and specialized lexicon reflect a long evolutionary history in Central Africa.

The Persian plateau served as hub for Homo sapiens after the main out of Africa dispersal

A combination of evidence, based on genetic, fossil and archaeological findings, indicates that Homo sapiens spread out of Africa between ~70-60 thousand years ago (kya). However, it appears that once outside of Africa, human populations did not expand across all of Eurasia until ~45 kya. The geographic whereabouts of these early settlers in the timeframe between ~70-60 to 45 kya has been difficult to reconcile. Here we combine genetic evidence and palaeoecological models to infer the geographic location that acted as the Hub for our species during the early phases of colonisation of Eurasia. Leveraging on available genomic evidence we show that populations from the Persian Plateau carry an ancestry component that closely matches the population that settled the Hub outside Africa. With the paleoclimatic data available to date, we built ecological models showing that the Persian Plateau was suitable for human occupation and that it could sustain a larger population compared to other West Asian regions, strengthening this claim.

The Allen Ancient DNA Resource (AADR) a curated compendium of ancient human genomes

More than two hundred papers have reported genome-wide data from ancient humans. While the raw data for the vast majority are fully publicly available testifying to the commitment of the paleogenomics community to open data, formats for both raw data and meta-data differ. There is thus a need for uniform curation and a centralized, version-controlled compendium that researchers can download, analyze, and reference. Since 2019, we have been maintaining the Allen Ancient DNA Resource (AADR), which aims to provide an up-to-date, curated version of the world's published ancient human DNA data, represented at more than a million single nucleotide polymorphisms (SNPs) at which almost all ancient individuals have been assayed. The AADR has gone through six public releases at the time of writing and review of this manuscript, and crossed the threshold of >10,000 individuals with published genome-wide ancient DNA data at the end of 2022. This note is intended as a citable descriptor of the AADR.

Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

BACKGROUND

The study of ancestral alleles provides insights into the evolutionary history, selection, and genetic structures of a population. In cattle, ancestral alleles are widely used in genetic analyses, including the detection of signatures of selection, determination of breed ancestry, and identification of admixture. Having a comprehensive list of ancestral alleles is expected to improve the accuracy of these genetic analyses. However, the list of ancestral alleles in cattle, especially at the whole genome sequence level, is far from complete. In fact, the current largest list of ancestral alleles (~ 42 million) represents less than 28% of the total number of detected variants in cattle. To address this issue and develop a genomic resource for evolutionary studies, we determined ancestral alleles in cattle by comparing prior derived whole-genome sequence variants to an out-species group using a population-based likelihood ratio test.

RESULTS

Our study determined and makes available the largest list of ancestral alleles in cattle to date (70.1 million) and includes 2.3 million on the X chromosome. There was high concordance (97.6%) of the determined ancestral alleles with those from previous studies when only high-probability ancestral alleles were considered (29.8 million positions) and another 23.5 million high-confidence ancestral alleles were novel, expanding the available reference list to improve the accuracies of genetic analyses involving ancestral alleles. The high concordance of the results with previous studies implies that our approach using genomic sequence variants and a likelihood ratio test to determine ancestral alleles is appropriate.

CONCLUSIONS

Considering the high concordance of ancestral alleles across studies, the ancestral alleles determined in this study including those not previously listed, particularly those with high-probability estimates, may be used for further genetic analyses with reasonable accuracy. Our approach that used predetermined variants in species and the likelihood ratio test to determine ancestral alleles is applicable to other species for which sequence level genotypes are available.

The genomic echoes of the last Green Sahara on the Fulani and Sahelian people

The population history of the Sahara/Sahelian belt is understudied, despite previous work highlighting complex dynamics.1,2,3,4,5,6,7 The Sahelian Fulani, i.e., the largest nomadic pastoral population in the world,8 represent an interesting case because they show a non-negligible proportion of an Eurasian genetic component, usually explained by recent admixture with northern Africans.1,2,5,6,7,9,10,11,12 Nevertheless, their origins are largely unknown, although several hypotheses have been proposed, including a possible link to ancient peoples settled in the Sahara during its last humid phase (Green Sahara, 12,000-5,000 years before present [BP]).13,14,15 To shed light about the Fulani ancient genetic roots, we produced 23 high-coverage (30×) whole genomes from Fulani individuals from 8 Sahelian countries, plus 17 samples from other African groups and 3 from Europeans as controls, for a total of 43 new whole genomes. These data have been compared with 814 published modern whole genomes2,16,17,18 and with relevant published ancient sequences (> 1,800 samples).19 These analyses showed some evidence that the non-sub-Saharan genetic ancestry component of the Fulani might have also been shaped by older events,1,5,6 possibly tracing the Fulani origins to unsampled ancient Green Saharan population(s). The joint analysis of modern and ancient samples allowed us to shed light on the genetic ancestry composition of such ancient Saharans, suggesting a similarity with Late Neolithic Moroccans and possibly pointing to a link with the spread of cattle herding. We also identified two different Fulani clusters whose admixture pattern may be informative about the historical Fulani movements and their later involvement in the western African empires.

Whole genomes from Angola and Mozambique inform about the origins and dispersals of major African migrations

As the continent of origin for our species, Africa harbours the highest levels of diversity anywhere on Earth. However, many regions of Africa remain under-sampled genetically. Here we present 350 whole genomes from Angola and Mozambique belonging to ten Bantu ethnolinguistic groups, enabling the construction of a reference variation catalogue including 2.9 million novel SNPs. We investigate the emergence of Bantu speaker population structure, admixture involving migrations across sub-Saharan Africa and model the demographic histories of Angolan and Mozambican Bantu speakers. Our results bring together concordant views from genomics, archaeology, and linguistics to paint an updated view of the complexity of the Bantu Expansion. Moreover, we generate reference panels that better represents the diversity of African populations involved in the trans-Atlantic slave trade, improving imputation accuracy in African Americans and Brazilians. We anticipate that our collection of genomes will form the foundation for future African genomic healthcare initiatives.

Diverse African genomes reveal selection on ancient modern human introgressions in Neanderthals

Comparisons of Neanderthal genomes to anatomically modern human (AMH) genomes show a history of Neanderthal-to-AMH introgression stemming from interbreeding after the migration of AMHs from Africa to Eurasia. All non-sub-Saharan African AMHs have genomic regions genetically similar to Neanderthals that descend from this introgression. Regions of the genome with Neanderthal similarities have also been identified in sub-Saharan African populations, but their origins have been unclear. To better understand how these regions are distributed across sub-Saharan Africa, the source of their origin, and what their distribution within the genome tells us about early AMH and Neanderthal evolution, we analyzed a dataset of high-coverage, whole-genome sequences from 180 individuals from 12 diverse sub-Saharan African populations. In sub-Saharan African populations with non-sub-Saharan African ancestry, as much as 1% of their genomes can be attributed to Neanderthal sequence introduced by recent migration, and subsequent admixture, of AMH populations originating from the Levant and North Africa. However, most Neanderthal homologous regions in sub-Saharan African populations originate from migration of AMH populations from Africa to Eurasia ∼250 kya, and subsequent admixture with Neanderthals, resulting in ∼6% AMH ancestry in Neanderthals. These results indicate that there have been multiple migration events of AMHs out of Africa and that Neanderthal and AMH gene flow has been bi-directional. Observing that genomic regions where AMHs show a depletion of Neanderthal introgression are also regions where Neanderthal genomes show a depletion of AMH introgression points to deleterious interactions between introgressed variants and background genomes in both groups-a hallmark of incipient speciation.

Modeling of African population history using f-statistics is biased when applying all previously proposed SNP ascertainment schemes

f-statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. Not only are they guaranteed to allow robust tests of the fits of proposed models of population history to data when analyzing full genome sequencing data-that is, all single nucleotide polymorphisms (SNPs) in the individuals being analyzed-but they are also guaranteed to allow robust tests of models for SNPs ascertained as polymorphic in a population that is an outgroup in a phylogenetic sense to all groups being analyzed. True "outgroup ascertainment" is in practice impossible in humans because our species has arisen from a substructured ancestral population that does not descend from a homogeneous ancestral population going back many hundreds of thousands of years into the past. However, initial studies suggested that non-outgroup-ascertainment schemes might produce robust enough results using f-statistics, and that motivated widespread fitting of models to data using non-outgroup-ascertained SNP panels such as the "Affymetrix Human Origins array" which has been genotyped on thousands of modern individuals from hundreds of populations, or the "1240k" in-solution enrichment reagent which has been the source of about 70% of published genome-wide data for ancient humans. In this study, we show that while analyses of population history using such panels work well for studies of relationships among non-African populations and one African outgroup, when co-modeling more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans), fitting of f-statistics to such SNP sets is expected to frequently lead to false rejection of true demographic histories, and failure to reject incorrect models. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, has limited statistical power and retains important biases. However, by carrying out simulations of diverse demographic histories, we show that bias in inferences based on f-statistics can be minimized by ascertaining on variants common in a union of diverse African groups; such ascertainment retains high statistical power while allowing co-analysis of archaic and modern groups.

Integrating equity frameworks into surgical quality improvement and health administrative databases: A narrative review

Ensuring safe, timely, and effective surgery is critical for high-quality healthcare and is the goal of surgical quality monitoring systems. At the heart of these systems are health administrative databases which house patient clinico-demographic information, healthcare processes and outcomes. Through analysis of monitoring systems outputs, we can identify gaps within healthcare delivery, patient experience, and surgical outcomes. However, gaps in our healthcare can only be measured by the variables we collect. Equity stratifiers are sociodemographic descriptors that can identify patient populations who experience differences in health and healthcare that may be considered unjust or unfair. They include age, education, gender, geographic location, income, Indigenous identity, racialized group, and sex at birth. These equity stratifiers represent measurable components of the social determinants of health housed within health administrative databases and allow for standardized analysis and reporting of health inequity. However, not all databases collect these stratifiers - making granular analysis of patient subgroups who may experience health inequity impossible to measure. Moreover, in databases that do collect this information, a wide range in the classification systems used makes for comparisons across jurisdictions challenging. The focus of this narrative review will be to apply the principles of the equity stratifier framework to examine what measures are collected in surgical quality improvement databases, cancer monitoring systems and provincial/state health administrative databases in the United States of America and Canada. The goal of this narrative review is to 1) inform researchers, surgeons, and policymakers of the current landscape of social variables collected within common health administrative databases. 2) Outline the pros and cons of the current collection system. 3) Issue a call to action for policymakers to incorporate health equity frameworks into the collection and reporting of data.

Genomic characterization of HLA class I and class II genes in ethnically diverse sub-Saharan African populations: A report on novel HLA alleles

HLA allelic variation has been well studied and documented in many parts of the world. However, African populations have been relatively under-represented in studies of HLA variation. We have characterized HLA variation from 489 individuals belonging to 13 ethnically diverse populations from rural communities from the African countries of Botswana, Cameroon, Ethiopia, and Tanzania, known to practice traditional subsistence lifestyles using next generation sequencing (Illumina) and long-reads from Oxford Nanopore Technologies. We identified 342 distinct alleles among the 11 HLA targeted genes: HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and -DPB1, with 140 of those alleles containing novel sequences that were submitted to the IPD-IMGT/HLA database. Sixteen of the 140 alleles contained novel content within the exonic regions of the genes, while 110 alleles contained novel intronic variants. Four alleles were found to be recombinants of already described HLA alleles and 10 alleles extended the sequence content of already described alleles. All 140 alleles include complete allelic sequence from the 5' UTR to the 3' UTR that are inclusive of all exons and introns. This report characterizes the HLA allelic variation from these individuals and describes the novel allelic variation present within these specific African populations.

The genetics of autism spectrum disorder in an East African familial cohort

Autism spectrum disorder (ASD) is a group of complex neurodevelopmental conditions affecting communication and social interaction in 2.3% of children. Studies that demonstrated its complex genetic architecture have been mainly performed in populations of European ancestry. We investigate the genetics of ASD in an East African cohort (129 individuals) from a population with higher prevalence (5%). Whole-genome sequencing identified 2.13 million private variants in the cohort and potentially pathogenic variants in known ASD genes (including CACNA1C, CHD7, FMR1, and TCF7L2). Admixture analysis demonstrated that the cohort comprises two ancestral populations, African and Eurasian. Admixture mapping discovered 10 regions that confer ASD risk on the African haplotypes, containing several known ASD genes. The increased ASD prevalence in this population suggests decreased heterogeneity in the underlying genetic etiology, enabling risk allele identification. Our approach emphasizes the power of African genetic variation and admixture analysis to inform the architecture of complex disorders.

Spatial and temporal diversity of positive selection on shared haplotypes at the PSCA locus among worldwide human populations

Selection on standing genetic variation is important for rapid local genetic adaptation when the environment changes. We report that, for the prostate stem cell antigen (PSCA) gene, different populations have different target haplotypes, even though haplotypes are shared among populations. The C-C-A haplotype, whereby the first C is located at rs2294008 of PSCA and is a low risk allele for gastric cancer, has become a target of positive selection in Asia. Conversely, the C-A-G haplotype carrying the same C allele has become a selection target mainly in Africa. However, Asian and African share both haplotypes, consistent with the haplotype divergence time (170 kya) prior to the out-of-Africa dispersal. The frequency of C-C-A/C-A-G is 0.344/0.278 in Asia and 0.209/0.416 in Africa. Two-dimensional site frequency spectrum analysis revealed that the extent of intra-allelic variability of the target haplotype is extremely small in each local population, suggesting that C-C-A or C-A-G is under ongoing hard sweeps in local populations. From the time to the most recent common ancestor (TMRCA) of selected haplotypes, the onset times of positive selection were recent (3-55 kya), concurrently with population subdivision from a common ancestor. Additionally, estimated selection coefficients from ABC analysis were up to ~3%, similar to those at other loci under recent positive selection. Phylogeny of local populations and TMRCA of selected haplotypes revealed that spatial and temporal switching of positive selection targets is a unique and novel feature of ongoing selection at PSCA. This switching may reflect the potential of rapid adaptability to distinct environments.

On whole-genome demography of world's ethnic groups and individual genomic identity

All current categorizations of human population, such as ethnicity, ancestry and race, are based on various selections and combinations of complex and dynamic common characteristics, that are mostly societal and cultural in nature, perceived by the members within or from outside of the categorized group. During the last decade, a massive amount of a new type of characteristics, that are exclusively genomic in nature, became available that allows us to analyze the inherited whole-genome demographics of extant human, especially in the fields such as human genetics, health sciences and medical practices (e.g., 1,2,3), where such health-related characteristics can be related to whole-genome-based categorization. Here we show the feasibility of deriving such whole-genome-based categorization. We observe that, within the available genomic data at present, (a) the study populations form about 14 genomic groups, each consisting of multiple ethnic groups; and (b), at an individual level, approximately 99.8%, on average, of the whole autosomal-genome contents are identical between any two individuals regardless of their genomic or ethnic groups.

Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture

Previous studies have highlighted how African genomes have been shaped by a complex series of historical events. Despite this, genome-wide data have only been obtained from a small proportion of present-day ethnolinguistic groups. By analyzing new autosomal genetic variation data of 1333 individuals from over 150 ethnic groups from Cameroon, Republic of the Congo, Ghana, Nigeria, and Sudan, we demonstrate a previously underappreciated fine-scale level of genetic structure within these countries, for example, correlating with historical polities in western Cameroon. By comparing genetic variation patterns among populations, we infer that many northern Cameroonian and Sudanese groups share genetic links with multiple geographically disparate populations, likely resulting from long-distance migrations. In Ghana and Nigeria, we infer signatures of intermixing dated to over 2000 years ago, corresponding to reports of environmental transformations possibly related to climate change. We also infer recent intermixing signals in multiple African populations, including Congolese, that likely relate to the expansions of Bantu language-speaking peoples.

Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation

We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.

Modeling of African population history using f -statistics can be highly biased and is not addressed by previously suggested SNP ascertainment schemes

f -statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. These statistics can provide strong evidence for either admixture or cladality, which can be robust to substantial rates of errors or missing data. f -statistics are guaranteed to be unbiased under "SNP ascertainment" (analyzing non-randomly chosen subsets of single nucleotide polymorphisms) only if it relies on a population that is an outgroup for all groups analyzed. However, ascertainment on a true outgroup that is not co-analyzed with other populations is often impractical and uncommon in the literature. In this study focused on practical rather than theoretical aspects of SNP ascertainment, we show that many non-outgroup ascertainment schemes lead to false rejection of true demographic histories, as well as to failure to reject incorrect models. But the bias introduced by common ascertainments such as the 1240K panel is mostly limited to situations when more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans) or non-human outgroups are co-modelled, for example, f 4 -statistics involving one non-African group, two African groups, and one archaic group. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, cannot fix all these problems since for some classes of f -statistics it is not a clean outgroup ascertainment, and in other cases it demonstrates relatively low power to reject incorrect demographic models since it provides a relatively small number of variants common in anatomically modern humans. And due to the paucity of high-coverage archaic genomes, archaic individuals used for ascertainment often act as sole representatives of the respective groups in an analysis, and we show that this approach is highly problematic. By carrying out large numbers of simulations of diverse demographic histories, we find that bias in inferences based on f -statistics introduced by non-outgroup ascertainment can be minimized if the derived allele frequency spectrum in the population used for ascertainment approaches the spectrum that existed at the root of all groups being co-analyzed. Ascertaining on sites with variants common in a diverse group of African individuals provides a good approximation to such a set of SNPs, addressing the great majority of biases and also retaining high statistical power for studying population history. Such a "pan-African" ascertainment, although not completely problem-free, allows unbiased exploration of demographic models for the widest set of archaic and modern human populations, as compared to the other ascertainment schemes we explored.

Coronavirus Host Genomics Study: South Africa (COVIGen-SA)

Host genetic factors are known to modify the susceptibility, severity, and outcomes of COVID-19 and vary across populations. However, continental Africans are yet to be adequately represented in such studies despite the importance of genetic factors in understanding Africa's response to the pandemic. We describe the development of a research resource for coronavirus host genomics studies in South Africa known as COVIGen-SA-a multicollaborator strategic partnership designed to provide harmonised demographic, clinical, and genetic information specific to Black South Africans with COVID-19. Over 2,000 participants have been recruited to date. Preliminary results on 1,354 SARS-CoV-2 positive participants from four participating studies showed that 64.7% were female, 333 had severe disease, and 329 were people living with HIV. Through this resource, we aim to provide insights into host genetic factors relevant to African-ancestry populations, using both genome-wide association testing and targeted sequencing of important genomic loci. This project will promote and enhance partnerships, build skills, and develop resources needed to address the COVID-19 burden and associated risk factors in South African communities.

Population interconnectivity over the past 120,000 years explains distribution and diversity of Central African hunter-gatherers

We combined ethnographic, archaeological, genetic, and paleoclimatic data to model the dynamics of Central African hunter-gatherer populations over the past 120,000 years. We show, against common assumptions, that their distribution and density are explained by changing environments rather than by a displacement following recent farming expansions, and that they have maintained large population sizes and genetic diversity, despite fluctuations in niche availability. Our results provide insights into the evolution of genetic and cultural diversity in Homo sapiens.

The evolutionary history of African hunter-gatherers holds key insights into modern human diversity. Here, we combine ethnographic and genetic data on Central African hunter-gatherers (CAHG) to show that their current distribution and density are explained by ecology rather than by a displacement to marginal habitats due to recent farming expansions, as commonly assumed. We also estimate the range of hunter-gatherer presence across Central Africa over the past 120,000 years using paleoclimatic reconstructions, which were statistically validated by our newly compiled dataset of dated archaeological sites. Finally, we show that genomic estimates of divergence times between CAHG groups match our ecological estimates of periods favoring population splits, and that recoveries of connectivity would have facilitated subsequent gene flow. Our results reveal that CAHG stem from a deep history of partially connected populations. This form of sociality allowed the coexistence of relatively large effective population sizes and local differentiation, with important implications for the evolution of genetic and cultural diversity in Homo sapiens.

Cross-ethnic analysis of common gene variants in hemostasis show lopsided representation of global populations in genetic databases

A majority of studies reporting human genetic variants were performed in populations of European ancestry whereas other global populations, and particularly many ethnolinguistic groups in other continents, are heavily underrepresented in these studies. To investigate the extent of this disproportionate representation of global populations concerning variants of significance to thrombosis and hemostasis, 845 single nucleotide polymorphisms (SNPs) in and around 34 genes associated with thrombosis and hemostasis and included in the commercial Axiom Precision Medicine Research Array (PMRA) were evaluated, using gene frequencies in 3 African (Somali and Luhya in East Africa, and Yoruba in West Africa) and 14 non-African (admixed American, East Asian, European, South Asian, and sub-groups) populations. Among the populations studied, Europeans were observed to be the best represented population by the hemostatic SNPs included in the PMRA. The European population also presented the largest number of common pharmacogenetic and pathogenic hemostatic variants reported in the ClinVar database. The number of such variants decreased the farther the genetic distance a population was from Europeans, with Yoruba and East Asians presenting the least number of clinically significant hemostatic SNPs in ClinVar while also being the two genetically most distinct populations from Europeans among the populations compared. Current study shows the lopsided representation of global populations as regards to hemostatic genetic variants listed in different commercial SNP arrays, such as the PMRA, and reported in genetic databases while also underlining the importance of inclusion of non-European ethnolinguistic populations in genomics studies designed to discover variants of significance to bleeding and thrombotic disorders.

Ancient DNA and deep population structure in sub-Saharan African foragers

Multiple lines of genetic and archaeological evidence suggest that there were major demographic changes in the terminal Late Pleistocene epoch and early Holocene epoch of sub-Saharan Africa^1–4. Inferences about this period are challenging to make because demographic shifts in the past 5,000 years have obscured the structures of more ancient populations^3,5. Here we present genome-wide ancient DNA data for six individuals from eastern and south-central Africa spanning the past approximately 18,000 years (doubling the time depth of sub-Saharan African ancient DNA), increase the data quality for 15 previously published ancient individuals and analyse these alongside data from 13 other published ancient individuals. The ancestry of the individuals in our study area can be modelled as a geographically structured mixture of three highly divergent source populations, probably reflecting Pleistocene interactions around 80–20 thousand years ago, including deeply diverged eastern and southern African lineages, plus a previously unappreciated ubiquitous distribution of ancestry that occurs in highest proportion today in central African rainforest hunter-gatherers. Once established, this structure remained highly stable, with limited long-range gene flow. These results provide a new line of genetic evidence in support of hypotheses that have emerged from archaeological analyses but remain contested, suggesting increasing regionalization at the end of the Pleistocene epoch.

DNA analysis of 6 individuals from eastern and south-central Africa spanning the past approximately 18,000 years, and of 28 previously published ancient individuals, provides genetic evidence supporting hypotheses of increasing regionalization at the end of the Pleistocene.

Disrupting Essentialism in Medical Genetics Education

Many traditional practices in medical genetics education need review to counteract messages of essentialism, or the belief in an underlying natural structure differentiating social categories. While genomics research increasingly disproves a genetic foundation for race, research from educational scholars demonstrates that current medical genetics instruction may actually reinforce racial bias in learners. In this monograph, we outline seven recommendations for medical educators to actively counteract essentialism, racial, and otherwise, in the genetics classroom. In particular, we emphasize the importance of engaging learners in nuanced discussions around stereotyping and its negative consequences for both accurate diagnoses and promoting health equity.

Advances in integrative African genomics

There has been a rapid increase in human genome sequencing in the past two decades, resulting in the identification of millions of previously unknown genetic variants. However, African populations are under-represented in sequencing efforts. Additional sequencing from diverse African populations and the construction of African-specific reference genomes is needed to better characterize the full spectrum of variation in humans. However, sequencing alone is insufficient to address the molecular and cellular mechanisms underlying variable phenotypes and disease risks. Determining functional consequences of genetic variation using multi-omics approaches is a fundamental post-genomic challenge. We discuss approaches to close the knowledge gaps about African genomic diversity and review advances in African integrative genomic studies and their implications for precision medicine.

Towards advancing African management scholarship

Purpose

This paper aims to address the main arguments put forward in Grietjie Verhoef’s article and contribute to a wider debate among management scholars on the role of indigenous theories. It challenges the view of African management as illusory and points to the rising support for indigenous theories as indicative of the weakening of the unquestioned dominance of universal theories.

Design/methodology/approach

This paper takes a conceptual and critically reflective approach, underpinned by a 360-degree evaluation of pertinent literature and theoretical arguments.

Findings

This paper reveals an underlying symmetry and interconnectedness, anchored on a shared communal ethos, among Afrocentric management concepts, specifically Ubuntu, Ekpe and Igbo apprenticeship systems. This symmetry points to an underlying indigenous management theory that begs to be further conceptualised, evidenced and advanced.

Research limitations/implications

This paper affirms Verhoef’s demand for Ubuntu, Ekpe, Igbo apprenticeship system to be more rigorously developed and theoretically coherent and urges scholars to intensify effort towards advancing the conceptual and empirical foundations of African management. Echoing Mahatma Gandhi’s timeless counsel, this paper calls on critics of African management to join the effort to bring about the change they wish to see in African management theorising.

Social implications

This paper disavows the alleged effort to impose a single “African management” model or perpetuate the “colonial/indigenous” binary divide but equally cautions against an effort to veto scholarly striving for a common identity, to learn from history or not embrace collective amnesia. As examples from the USA and Europe show, diversity, even heterogeneity, needs not to preclude the forging of a commonly shared identity complemented with appropriate sub-identities.

Originality/value

This paper links the African management-centred themes addressed by Verhoef to the wider debate among management scholars about lessening the dominance of universal theories and allowing space for context-resonant indigenous theories. It calls on African management scholars to invest the premium and intensified effort towards building a more robust and coherent body of indigenous theory that will have the capacity and efficacy to inform, explain and advance organisational practice and outcomes across Africa.

Population Structure of the South West Indian Ocean Islands: Implications for Precision Medicine

Precision medicine has brought new hopes for patients around the world with the applications of novel technologies for understanding genetics of complex diseases and their translation into clinical services. Such applications however require a foundation of skills, knowledge and infrastructure to translate genetics for health care. The crucial element is no doubt the availability of genomics data for the target populations, which is seriously lacking for most parts of Africa. We discuss here why it is vital to prioritize genomics data for the South West Indian Ocean region where a mosaic of ethnicities co-exist. The islands of the SWIO, which comprise Madagascar, La Reunion, Mauritius, Seychelles and Comoros, have been the scene for major explorations and trade since the 17th century being on the route to Asia. This part of the world has lived through active passage of slaves from East Africa to Arabia and further. Today’s demography of the islands is a diverse mix of ancestries including European, African and Asian. The extent of admixtures has yet to be resolved. Except for a few studies in Madagascar, there is very little published data on human genetics for these countries. Isolation and small population sizes have likely resulted in reduced genetic variation and possible founder effects. There is a significant prevalence of diabetes, particularly in individuals of Indian descent, while breast and prostate cancers are on the rise. The island of La Reunion is a French overseas territory with a high standard of health care and close ties to Mauritius. Its demography is comparable to that of Mauritius but with a predominantly mixed population and a smaller proportion of people of Indian descent. On the other hand, Madagascar’s African descendants inhabit mostly the lower coastal zones of the West and South regions, while the upper highlands are occupied by peoples of mixed African-Indonesian ancestries. Historical records confirm the Austronesian contribution to the Madagascar genomes. With the rapid progress in genomic medicine, there is a growing demand for sequencing services in the clinical settings to explore the incidence of variants in candidate disease genes and other markers. Genome sequence data has become a priority in order to understand the population sub-structures and to identify specific pathogenic variants among the different groups of inhabitants on the islands. Genomic data is increasingly being used to advise families at risk and propose diagnostic screening measures to enhance the success of therapies. This paper discusses the complexity of the islands’ populations and argues for the needs for genotyping and understanding the genetic factors associated with disease risks. The benefits to patients and improvement in health services through a concerted regional effort are depicted. Some private patients are having recourse to external facilities for molecular profiling with no return of data for research. Evidence of disease variants through sequencing represents a valuable source of medical data that can guide policy decisions at the national level. There are presently no such records for future implementation of strategies for genomic medicine.

Local ancestry prediction with PyLAE

Summary

We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations.

Availability and implementation

The source code and installation manual are available at https://github.com/smetam/pylae.

A reference database of forensic autosomal and gonosomal STR markers in the Tigray population of Ethiopia

Allele frequencies of 21 autosomal STR markers (AmpF/STR GlobalFiler) and haplotype frequencies of 27 Y- and 12 X-STR markers (AmpF/STR YFiler Plus and Investigator Argus X-12, respectively) were investigated in the Tigray population of Ethiopia, representing the main population group in the Tigray regional state of Ethiopia and neighboring Eritrea. For autosomal STR allele frequencies, the average random match probability in the Tigray sample was 2.1 × 10^-27. The average locus by locus F_ST distance calculated comparing autosomal STR allele frequencies from Tigray and from a broad regional reference dataset currently available for the Horn of Africa was 0.003. The Tigray male sample displayed high Y-STR diversity, with complete individualization of haplotypes using the AmpF/STR YFiler Plus panel. Analysis of molecular variance did not detect significant heterogeneity between Y-STR haplotypes observed in the present study and those previously reported in the literature for other Tigray population samples from Ethiopia and Eritrea. Study of the X-STR landscape in Tigray evidenced several distinctive features including: the molecular characterization of a novel null allele at locus DXS10146 with frequency > 1%; allele dependency between loci within linkage groups I and III; significant differences in haplotype distribution compared to other Horn of Africa populations, that should be taken into account in kinship analysis. The collected data can be used as a reference STR database by local forensic genetics services and in genetic identification procedures of victims of human trafficking in the Mediterranean Sea, which frequently involve individuals originating from the Horn of Africa.

Comparison of sequencing data processing pipelines and application to underrepresented African human populations

Background

Population genetic studies of humans make increasing use of high-throughput sequencing in order to capture diversity in an unbiased way. There is an abundance of sequencing technologies, bioinformatic tools and the available genomes are increasing in number. Studies have evaluated and compared some of these technologies and tools, such as the Genome Analysis Toolkit (GATK) and its “Best Practices” bioinformatic pipelines. However, studies often focus on a few genomes of Eurasian origin in order to detect technical issues. We instead surveyed the use of the GATK tools and established a pipeline for processing high coverage full genomes from a diverse set of populations, including Sub-Saharan African groups, in order to reveal challenges from human diversity and stratification.

Results

We surveyed 29 studies using high-throughput sequencing data, and compared their strategies for data pre-processing and variant calling. We found that processing of data is very variable across studies and that the GATK “Best Practices” are seldom followed strictly. We then compared three versions of a GATK pipeline, differing in the inclusion of an indel realignment step and with a modification of the base quality score recalibration step. We applied the pipelines on a diverse set of 28 individuals. We compared the pipelines in terms of count of called variants and overlap of the callsets. We found that the pipelines resulted in similar callsets, in particular after callset filtering. We also ran one of the pipelines on a larger dataset of 179 individuals. We noted that including more individuals at the joint genotyping step resulted in different counts of variants. At the individual level, we observed that the average genome coverage was correlated to the number of variants called.

Conclusions

We conclude that applying the GATK “Best Practices” pipeline, including their recommended reference datasets, to underrepresented populations does not lead to a decrease in the number of called variants compared to alternative pipelines. We recommend to aim for coverage of > 30X if identifying most variants is important, and to work with large sample sizes at the variant calling stage, also for underrepresented individuals and populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04407-x.

Evolutionary perspectives on African North American genetic diversity: Origins and prospects for future investigations

African-descended peoples of the Americas represent an amalgamation of West, Central, and Southeast African regional and ethnic groups with modest gene flow from specific non-African populations. Despite 16+ generations of residence in the Americas, there is a deficit of evolutionary knowledge about these populations. Focusing on Legacy African American, the African North American descendants of survivors of the transatlantic trade in enslaved Africans, we report on emic evolutionary perspectives of their self-identity gleaned from our interviews of 600 individuals collected over 2 years. Gullah-Geechee peoples of Carolina Coastal regions are a model case study due to their historical antiquity, substantial African retentions, relative geospatial isolation, and proposed progenitor status to other Legacy African American microethnic groups. We identify salient research questions for future studies that will begin to bridge the evolutionary gaps in our knowledge of these diverse peoples and the historical evidence for specific evolutionary processes.

African Global Representation in Biomedical Sciences

African populations are diverse in their ethnicity, language, culture, and genetics. Although plagued by high disease burdens, until recently the continent has largely been excluded from biomedical studies. Along with limitations in research and clinical infrastructure, human capacity, and funding, this omission has resulted in an underrepresentation of African data and disadvantaged African scientists. This review interrogates the relative abundance of biomedical data from Africa, primarily in genomics and other omics. The visibility of African science through publications is also discussed. A challenge encountered in this review is the relative lack of annotation of data on their geographical or population origin, with African countries represented as a single group. In addition to the abovementioned limitations,the global representation of African data may also be attributed to the hesitation to deposit data in public repositories. Whatever the reason, the disparity should be addressed, as African data have enormous value for scientists in Africa and globally.

The Simons Genome Diversity Project: A Global Analysis of Mobile Element Diversity

Ongoing retrotransposition of Alu, LINE-1, and SINE–VNTR–Alu elements generates diversity and variation among human populations. Previous analyses investigating the population genetics of mobile element insertions (MEIs) have been limited by population ascertainment bias or by relatively small numbers of populations and low sequencing coverage. Here, we use 296 individuals representing 142 global populations from the Simons Genome Diversity Project (SGDP) to discover and characterize MEI diversity from deeply sequenced whole-genome data. We report 5,742 MEIs not originally reported by the 1000 Genomes Project and show that high sampling diversity leads to a 4- to 7-fold increase in MEI discovery rates over the original 1000 Genomes Project data. As a result of negative selection, nonreference polymorphic MEIs are underrepresented within genes, and MEIs within genes are often found in the transcriptional orientation opposite that of the gene. Globally, 80% of Alu subfamilies predate the expansion of modern humans from Africa. Polymorphic MEIs show heterozygosity gradients that decrease from Africa to Eurasia to the Americas, and the number of MEIs found uniquely in a single individual are also distributed in this general pattern. The maximum fraction of MEI diversity partitioned among the seven major SGDP population groups (F_ST) is 7.4%, similar to, but slightly lower than, previous estimates and likely attributable to the diverse sampling strategy of the SGDP. Finally, we utilize these MEIs to extrapolate the primary Native American shared ancestry component to back to Asia and provide new evidence from genome-wide identical-by-descent genetic markers that add additional support for a southeastern Siberian origin for most Native Americans.

Our Tangled Family Tree: New Genomic Methods Offer Insight into the Legacy of Archaic Admixture

The archaic ancestry present in the human genome has captured the imagination of both scientists and the wider public in recent years. This excitement is the result of new studies pushing the envelope of what we can learn from the archaic genetic information that has survived for over 50,000 years in the human genome. Here, we review the most recent ten years of literature on the topic of archaic introgression, including the current state of knowledge on Neanderthal and Denisovan introgression, as well as introgression from other as-yet unidentified archaic populations. We focus this review on four topics: 1) a reimagining of human demographic history, including evidence for multiple admixture events between modern humans, Neanderthals, Denisovans, and other archaic populations; 2) state-of-the-art methods for detecting archaic ancestry in population-level genomic data; 3) how these novel methods can detect archaic introgression in modern African populations; and 4) the functional consequences of archaic gene variants, including how those variants were co-opted into novel function in modern human populations. The goal of this review is to provide a simple-to-access reference for the relevant methods and novel data, which has changed our understanding of the relationship between our species and its siblings. This body of literature reveals the large degree to which the genetic legacy of these extinct hominins has been integrated into the human populations of today.

An ancestral recombination graph of human, Neanderthal, and Denisovan genomes

Many humans carry genes from Neanderthals, a legacy of past admixture. Existing methods detect this archaic hominin ancestry within human genomes using patterns of linkage disequilibrium or direct comparison to Neanderthal genomes. Each of these methods is limited in sensitivity and scalability. We describe a new ancestral recombination graph inference algorithm that scales to large genome-wide datasets and demonstrate its accuracy on real and simulated data. We then generate a genome-wide ancestral recombination graph including human and archaic hominin genomes. From this, we generate a map within human genomes of archaic ancestry and of genomic regions not shared with archaic hominins either by admixture or incomplete lineage sorting. We find that only 1.5 to 7% of the modern human genome is uniquely human. We also find evidence of multiple bursts of adaptive changes specific to modern humans within the past 600,000 years involving genes related to brain development and function.

African genetic diversity and adaptation inform a precision medicine agenda

The deep evolutionary history of African populations, since the emergence of modern humans more than 300,000 years ago, has resulted in high genetic diversity and considerable population structure. Selected genetic variants have increased in frequency due to environmental adaptation, but recent exposures to novel pathogens and changes in lifestyle render some of them with properties leading to present health liabilities. The unique discoverability potential from African genomic studies promises invaluable contributions to understanding the genomic and molecular basis of health and disease. Globally, African populations are understudied, and precision medicine approaches are largely based on data from European and Asian-ancestry populations, which limits the transferability of findings to the continent of Africa. Africa needs innovative precision medicine solutions based on African data that use knowledge and implementation strategies aligned to its climatic, cultural, economic and genomic diversity.

Structure and ancestry patterns of Ethiopians in genome-wide autosomal DNA

We review some of the current insights derived from the analyses of new large-scale, genome-wide autosomal variation data studies incorporating Ethiopians. Consistent with their substantial degree of cultural and linguistic diversity, genetic diversity among Ethiopians is higher than that seen across much larger geographic regions worldwide. This genetic variation is associated in part with ethnic identity, geography and linguistic classification. Numerous and varied admixture events have been inferred in Ethiopian groups, for example, involving sources related to present-day groups in West Eurasia and North Africa, with inferred dates spanning a few hundred to more than 4500 years ago. These disparate inferred ancestry patterns are correlated in part with groups' broad linguistic classifications, though with some notable exceptions. While deciphering these complex genetic signals remains challenging with available data, these studies and other projects focused on resolving competing hypotheses on the origins of specific ethnolinguistic groups demonstrate how genetic analyses can complement findings from anthropological and linguistic studies on Ethiopians.

The deep population history in Africa

Africa is the continent with the greatest genetic diversity among humans and the level of diversity is further enhanced by incorporating non-majority groups, which are often understudied. Many of today's minority populations historically practiced foraging lifestyles, which were the only subsistence strategies prior to the rise of agriculture and pastoralism, but only a few groups practicing these strategies remain today. Genomic investigations of Holocene human remains excavated across the African continent show that the genetic landscape was vastly different compared to today's genetic landscape and that many groups that today are population isolate inhabited larger regions in the past. It is becoming clear that there are periods of isolation among groups and geographic areas, but also genetic contact over large distances throughout human history in Africa. Genomic information from minority populations and from prehistoric remains provide an invaluable source of information on the human past, in particular deep human population history, as Holocene large-scale population movements obscure past patterns of population structure. Here we revisit questions on the nature and time of the radiation of early humans in Africa, the extent of gene-flow among human populations as well as introgression from archaic and extinct lineages on the continent.

A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data

Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.

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

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.

Small body size phenotypes among Middle and Later Stone Age Southern Africans

Modern humans originated between 300 and 200 ka in structured populations throughout Africa, characterized by regional interaction and diversity. Acknowledgment of this complex Pleistocene population structure raises new questions about the emergence of phenotypic diversity. Holocene Southern African Later Stone Age (LSA) skeletons and descendant Khoe-San peoples have small adult body sizes that may reflect long-term adaptation to the Cape environment. Pleistocene Southern African adult body sizes are not well characterized, but some postcranial elements are available. The most numerous Pleistocene postcranial skeletal remains come from Klasies River Mouth on the Southern Cape coast of South Africa. We compare the morphology of these skeletal elements with globally sampled Holocene groups encompassing diverse adult body sizes and shapes (n = 287) to investigate whether there is evidence for phenotypic patterning. The adult Klasies River Mouth bones include most of a lumbar vertebra, and portions of a left clavicle, left proximal radius, right proximal ulna, and left first metatarsal. Linear dimensions, shape characteristics, and cross-sectional geometric properties of the Klasies River Mouth elements were compared using univariate and multivariate methods. Between-group principal component analyses group Klasies River Mouth elements, except the proximal ulna, with LSA Southern Africans. The similarity is driven by size. Klasies River Mouth metatarsal cross-sectional geometric properties indicate similar torsional and compressive strength to those from LSA Southern Africans. Phenotypic expressions of small-bodied adult morphology in Marine Isotope Stages 5 and 1 suggest this phenotype may represent local convergent adaptation to life in the Cape.

Origins of modern human ancestry

New finds in the palaeoanthropological and genomic records have changed our view of the origins of modern human ancestry. Here we review our current understanding of how the ancestry of modern humans around the globe can be traced into the deep past, and which ancestors it passes through during our journey back in time. We identify three key phases that are surrounded by major questions, and which will be at the frontiers of future research. The most recent phase comprises the worldwide expansion of modern humans between 40 and 60 thousand years ago (ka) and their last known contacts with archaic groups such as Neanderthals and Denisovans. The second phase is associated with a broadly construed African origin of modern human diversity between 60 and 300 ka. The oldest phase comprises the complex separation of modern human ancestors from archaic human groups from 0.3 to 1 million years ago. We argue that no specific point in time can currently be identified at which modern human ancestry was confined to a limited birthplace, and that patterns of the first appearance of anatomical or behavioural traits that are used to define Homo sapiens are consistent with a range of evolutionary histories.

Sub-Saharan African information potential to unveil adaptations to infectious disease

Sub-Saharan Africa is the most promising region of the world to conduct high-throughput studies to unveil adaptations to infectious diseases due to several reasons, namely, the longest evolving time-depth in the Homo sapiens phylogenetic tree (at least two-third older than any other worldwide region); the continuous burden of infectious diseases (still number one in health/life threat); and the coexistence of populations practising diverse subsistence modes (nomadic or seminomadic hunter-gatherers and agropastoralists, and sedentary agriculturalists, small urban and megacity groups). In this review, we will present the most up-to-date results that shed light on three main hypotheses related with this adaptation. One is the hypothesis of coevolution between host and pathogen, given enough time for the establishment of this highly dynamic relationship. The second hypothesis enunciates that the agricultural transition was responsible for the increase of the infectious disease burden, due to the huge expansion of the sedentary human population and the cohabitation with domesticates as main reservoirs of pathogens. The third hypothesis states that the boosting of our immune system against pathogens by past selection may have resulted in maladaptation of the developed hygienic societies, leading to an increase of allergic, inflammatory and autoimmune disorders. Further work will enlighten the biological mechanisms behind these main adaptations, which can be insightful for translation into diagnosis, prognosis and treatment interventions.

Long Runs of Homozygosity Are Correlated with Marriage Preferences across Global Population Samples

Children of consanguineous unions carry long runs of homozygosity (ROH) in their genomes, due to their parents' recent shared ancestry. This increases the burden of recessive disease in populations with high levels of consanguinity and has been heavily studied in some groups. However, there has been little investigation of the broader effect of consanguinity on patterns of genetic variation on a global scale. This study, which collected published genetic data and information about marriage practice from 395 worldwide populations, shows that reported preference for cousin marriage has a detectable association with the distribution of long ROH in this sample, increasing the expected number of ROH longer than 10 cM by a factor of 2.2. Variation in marriage practice and consequent rates of consanguinity are therefore an important aspect of demographic history for the purposes of modeling human genetic variation. However, reported marriage practices explain a relatively small proportion of the variation in ROH distribution, and consequently, population genetic data are only partially informative about cultural preferences.

Inauguration of the Tanzania Society of Human Genetics: Biomedical Research in Tanzania with Emphasis on Human Genetics and Genomics

Human genetics research and applications are rapidly growing areas in health innovations and services. African populations are reported to be highly diverse and carry the greatest number of variants per genome. Exploring these variants is key to realize the genomic medicine initiative. However, African populations are grossly underrepresented in various genomic databases, which has alerted scientists to address this issue with urgency. In Tanzania, human genetics research and services are conducted in different institutions on both communicable and noncommunicable diseases. However, there is poor coordination of the research activities, often leading to limited application of the research findings and poor utilization of available resources. In addition, contributions from Tanzanian human genetics research and services are not fully communicated to the government, national, and international communities. To address this scientific gap, the Tanzania Society of Human Genetics (TSHG) has been formed to bring together all stakeholders of human genetics activities in Tanzania and to formally bring Tanzania as a member to the African Society of Human Genetics. This article describes the inauguration event of the TSHG, which took place in November 2019. It provides a justification for its establishment and discusses presentations from invited speakers who took part in the inauguration of the TSHG.

Population history of North Africa based on modern and ancient genomes

Compared with the rest of the African continent, North Africa has provided limited genomic data. Nonetheless, the genetic data available show a complex demographic scenario characterized by extensive admixture and drift. Despite the continuous gene flow from the Middle East, Europe and sub-Saharan Africa, an autochthonous genetic component that dates back to pre-Holocene times is still present in North African groups. The comparison of ancient and modern genomes has evidenced a genetic continuity in the region since Epipaleolithic times. Later population movements, especially the gene flow from the Middle East associated with the Neolithic, have diluted the genetic autochthonous component, creating an east to west gradient. Recent historical movements, such as the Arabization, have also contributed to the genetic landscape observed currently in North Africa and have culturally transformed the region. Genome analyses have not shown evidence of a clear correlation between cultural and genetic diversity in North Africa, as there is no genetic pattern of differentiation between Tamazight (i.e. Berber) and Arab speakers as a whole. Besides the gene flow received from neighboring areas, the analysis of North African genomes has shown that the region has also acted as a source of gene flow since ancient times. As a result of the genetic uniqueness of North African groups and the lack of available data, there is an urgent need for the study of genetic variation in the region and its implications in health and disease.

Closing the Gaps in Genomic Research

Despite Africa's central role in the origin of our species, our knowledge of the genomic diversity in Africa is remarkably sparse. A recent publication by Choudhury et al. underscores the scientific imperative for a broader characterisation of African genomic diversity to better understand demographic history and improve global human health.

Global Picture of Genetic Relatedness and the Evolution of Humankind

Simple Summary

The intricacies of human ancestry are buried deep within our DNA. For years, scientists have been working to piece together a vast picture of our genetic lineage. The purpose of this study was to further reveal this global picture of human genetic relatedness using identical-by-descent (IBD) genomic fragments. We processed over 65 million very rare single nucleotide polymorphic (SNP) alleles and detected over 17 million shared IBD fragments, including very short IBD fragments that allowed us to trace common ancestors back to 200,000 years ago. We also determined nine geographical regions representing nine unique genetic components for mankind: East and West Africa, Northern Europe, Arctica, East Asia, Oceania, South Asia, Middle East, and South America. The levels of admixture in every studied population could be assigned to one of these regions and long-term neighboring populations are strikingly similar, despite any political, religious, and cultural differences. Additionally, we observed the topmost admixture to be in central Eurasia. The entire picture of relatedness of all the studied populations presents itself in the form of shared number/size of IBDs, providing novel insights into geographical admixtures and genetic contributions that shaped human ancestry into what it is today.

Abstract

We performed an exhaustive pairwise comparison of whole-genome sequences of 3120 individuals, representing 232 populations from all continents and seven prehistoric people including archaic and modern humans. In order to reveal an intricate picture of worldwide human genetic relatedness, 65 million very rare single nucleotide polymorphic (SNP) alleles have been bioinformatically processed. The number and size of shared identical-by-descent (IBD) genomic fragments for every pair of 3127 individuals have been revealed. Over 17 million shared IBD fragments have been described. Our approach allowed detection of very short IBD fragments (<20 kb) that trace common ancestors who lived up to 200,000 years ago. We detected nine distinct geographical regions within which individuals had strong genetic relatedness, but with negligible relatedness between the populations of these regions. The regions, comprising nine unique genetic components for mankind, are the following: East and West Africa, Northern Europe, Arctica, East Asia, Oceania, South Asia, Middle East, and South America. The level of admixture in every studied population has been apportioned among these nine genetic components. Genetically, long-term neighboring populations are strikingly similar to each other in spite of any political, religious, and cultural differences. The topmost admixture has been observed at the center of Eurasia. These admixed populations (including Uyghurs, Azerbaijanis, Uzbeks, and Iranians) have roughly equal genetic contributions from the Middle East, Europe, China, and India, with additional significant traces from Africa and Arctic. The entire picture of relatedness of all the studied populations unfolds and presents itself in the form of shared number/size of IBDs.

The genomic prehistory of peoples speaking Khoisan languages

Peoples speaking so-called Khoisan languages-that is, indigenous languages of southern Africa that do not belong to the Bantu family-are culturally and linguistically diverse. They comprise herders, hunter-gatherers as well as groups of mixed modes of subsistence, and their languages are classified into three distinct language families. This cultural and linguistic variation is mirrored by extensive genetic diversity. We here review the recent genomics literature and discuss the genetic evidence for a formerly wider geographic spread of peoples with Khoisan-related ancestry, for the deep divergence among populations speaking Khoisan languages overlaid by more recent gene flow among these groups and for the impact of admixture with immigrant food-producers in their prehistory.

Type 1 diabetes in Africa: an immunogenetic study in the Amhara of North-West Ethiopia

AIMS/HYPOTHESIS

We aimed to characterise the immunogenic background of insulin-dependent diabetes in a resource-poor rural African community. The study was initiated because reports of low autoantibody prevalence and phenotypic differences from European-origin cases with type 1 diabetes have raised doubts as to the role of autoimmunity in this and similar populations.

METHODS

A study of consecutive, unselected cases of recently diagnosed, insulin-dependent diabetes (n = 236, ≤35 years) and control participants (n = 200) was carried out in the ethnic Amhara of rural North-West Ethiopia. We assessed their demographic and socioeconomic characteristics, and measured non-fasting C-peptide, diabetes-associated autoantibodies and HLA-DRB1 alleles. Leveraging genome-wide genotyping, we performed both a principal component analysis and, given the relatively modest sample size, a provisional genome-wide association study. Type 1 diabetes genetic risk scores were calculated to compare their genetic background with known European type 1 diabetes determinants.

RESULTS

Patients presented with stunted growth and low BMI, and were insulin sensitive; only 15.3% had diabetes onset at ≤15 years. C-peptide levels were low but not absent. With clinical diabetes onset at ≤15, 16-25 and 26-35 years, 86.1%, 59.7% and 50.0% were autoantibody positive, respectively. Most had autoantibodies to GAD (GADA) as a single antibody; the prevalence of positivity for autoantibodies to IA-2 (IA-2A) and ZnT8 (ZnT8A) was low in all age groups. Principal component analysis showed that the Amhara genomes were distinct from modern European and other African genomes. HLA-DRB1*03:01 (p = 0.0014) and HLA-DRB1*04 (p = 0.0001) were positively associated with this form of diabetes, while HLA-DRB1*15 was protective (p < 0.0001). The mean type 1 diabetes genetic risk score (derived from European data) was higher in patients than control participants (p = 1.60 × 10-7). Interestingly, despite the modest sample size, autoantibody-positive patients revealed evidence of association with SNPs in the well-characterised MHC region, already known to explain half of type 1 diabetes heritability in Europeans.

CONCLUSIONS/INTERPRETATION

The majority of patients with insulin-dependent diabetes in rural North-West Ethiopia have the immunogenetic characteristics of autoimmune type 1 diabetes. Phenotypic differences between type 1 diabetes in rural North-West Ethiopia and the industrialised world remain unexplained.

High Levels of Genetic Diversity within Nilo-Saharan Populations: Implications for Human Adaptation

Africa contains more human genetic variation than any other continent, but the majority of the population-scale analyses of the African peoples have focused on just two of the four major linguistic groups, the Niger-Congo and Afro-Asiatic, leaving the Nilo-Saharan and Khoisan populations under-represented. In order to assess genetic variation and signatures of selection within a Nilo-Saharan population and between the Nilo-Saharan and Niger-Congo and Afro-Asiatic, we sequenced 50 genomes from the Nilo-Saharan Lugbara population of North-West Uganda and 250 genomes from 6 previously unsequenced Niger-Congo populations. We compared these data to data from a further 16 Eurasian and African populations including the Gumuz, another putative Nilo-Saharan population from Ethiopia. Of the 21 million variants identified in the Nilo-Saharan population, 3.57 million (17%) were not represented in dbSNP and included predicted non-synonymous mutations with possible phenotypic effects. We found greater genetic differentiation between the Nilo-Saharan Lugbara and Gumuz populations than between any two Afro-Asiatic or Niger-Congo populations. F3 tests showed that Gumuz contributed a genetic component to most Niger-Congo B populations whereas Lugabara did not. We scanned the genomes of the Lugbara for evidence of selective sweeps. We found selective sweeps at four loci (SLC24A5, SNX13, TYRP1, and UVRAG) associated with skin pigmentation, three of which already have been reported to be under selection. These selective sweeps point toward adaptations to the intense UV radiation of the Sahel.

Population bias in somatic measurement of microsatellite instability status

Microsatellite instability (MSI) is a key secondary effect of a defective DNA mismatch repair mechanism resulting in incorrectly replicated microsatellites in many malignant tumors. Historically, MSI detection has been performed by fragment analysis (FA) on a panel of representative genomic markers. More recently, using next-generation sequencing (NGS) to analyze thousands of microsatellites has been shown to improve the robustness and sensitivity of MSI detection. However, NGS-based MSI tests can be prone to population biases if NGS results are aligned to a reference genome instead of patient-matched normal tissue. We observed an increased rate of false positives in patients of African ancestry with an NGS-based diagnostic for MSI status utilizing 7317 microsatellite loci. We then minimized this bias by training a modified calling model that utilized 2011 microsatellite loci. With these adjustments 100% (95% CI: 89.1% to 100%) of African ancestry patients in an independent validation test were called correctly using the updated model. This poses not only a significant technical improvement but also has an important clinical impact on directing immune checkpoint inhibitor therapy.

Applying f4 -statistics and admixture graphs: Theory and examples

A popular approach to learning about admixture from population genetic data is by computing the allele-sharing summary statistics known as f-statistics. Compared to some methods in population genetics, f-statistics are relatively simple, but interpreting them can still be complicated at times. In addition, f-statistics can be used to build admixture graphs (multi-population trees allowing for admixture events), which provide more explicit and thorough modelling capabilities but are correspondingly more complex to work with. Here, I discuss some of these issues to provide users of these tools with a basic guide for protocols and procedures. My focus is on the kinds of conclusions that can or cannot be drawn from the results of f₄ -statistics and admixture graphs, illustrated with real-world examples involving human populations.