Malaria was a weak selective force in ancient Europeans

Intra-individual variability in ancient plasmodium DNA recovery highlights need for enhanced sampling

Malaria has been a leading cause of death in human populations for centuries and remains a major public health challenge in African countries, especially affecting children. Among the five Plasmodium species infecting humans, Plasmodium falciparum is the most lethal. Ancient DNA research has provided key insights into the origins, evolution, and virulence of pathogens that affect humans. However, extensive screening of ancient skeletal remains for Plasmodium DNA has shown that such genomic material is rare, with no studies so far addressing potential intra-individual variability. Consequently, the pool of ancient mitochondrial DNA (mtDNA) or genomic sequences for P. falciparum is extremely limited, with fewer than 20 ancient sequences available for genetic analysis, and no complete P. falciparum mtDNA from Classical antiquity published to date. To investigate intra-individual diversity and genetic origins of P. falciparum from the Roman period, we generated 39 sequencing libraries from multiple teeth and two from the femur of a Roman malaria-infected individual. The results revealed considerable variability in P. falciparum recovery across different dental samples within the individual, while the femur samples showed no preservation of Plasmodium DNA. The reconstructed 43-fold P. falciparum mtDNA genome supports the hypothesis of an Indian origin for European P. falciparum and suggests mtDNA continuity in Europe over the past 2000 years.

Ancient Plasmodium genomes shed light on the history of human malaria

Malaria-causing protozoa of the genus Plasmodium have exerted one of the strongest selective pressures on the human genome, and resistance alleles provide biomolecular footprints that outline the historical reach of these species1. Nevertheless, debate persists over when and how malaria parasites emerged as human pathogens and spread around the globe1,2. To address these questions, we generated high-coverage ancient mitochondrial and nuclear genome-wide data from P. falciparum, P. vivax and P. malariae from 16 countries spanning around 5,500 years of human history. We identified P. vivax and P. falciparum across geographically disparate regions of Eurasia from as early as the fourth and first millennia BCE, respectively; for P. vivax, this evidence pre-dates textual references by several millennia3. Genomic analysis supports distinct disease histories for P. falciparum and P. vivax in the Americas: similarities between now-eliminated European and peri-contact South American strains indicate that European colonizers were the source of American P. vivax, whereas the trans-Atlantic slave trade probably introduced P. falciparum into the Americas. Our data underscore the role of cross-cultural contacts in the dissemination of malaria, laying the biomolecular foundation for future palaeo-epidemiological research into the impact of Plasmodium parasites on human history. Finally, our unexpected discovery of P. falciparum in the high-altitude Himalayas provides a rare case study in which individual mobility can be inferred from infection status, adding to our knowledge of cross-cultural connectivity in the region nearly three millennia ago.

The millennial dynamics of malaria in the mediterranean basin: documenting Plasmodium spp. on the medieval island of Corsica

Introduction

The lack of well-preserved material upon which to base the paleo-microbiological detection of Plasmodium parasites has prevented extensive documentation of past outbreaks of malaria in Europe. By trapping intact erythrocytes at the time of death, dental pulp has been shown to be a suitable tissue for documenting ancient intraerythrocytic pathogens such as Plasmodium parasites.

Methods

Total DNA and proteins extracted from 23 dental pulp specimens collected from individuals exhumed from the 9th to 13th century archaeological site in Mariana, Corsica, were analyzed using open-mind paleo-auto-immunohistochemistry and direct metagenomics, Plasmodium-targeting immunochromatography assays. All experiments incorporated appropriate negative controls.

Results

Paleo-auto-immunohistochemistry revealed the presence of parasites Plasmodium spp. in the dental pulp of nine teeth. A further immunochromatography assay identified the presence of at least one Plasmodium antigen in nine individuals. The nine teeth, for which the PfHRP-2 antigen specific of P. falciparum was detected, were also positive using paleo-autoimmunohistochemistry and metagenomics.

Conclusion

Dental pulp erythrocytes proved to be suitable for the direct paleomicrobiology documentation of malaria in nine individuals buried in medieval Corsica, in agreement with historical data. This provides additional information on the millennial dynamics of Plasmodium spp. in the Mediterranean basin.

A Non-Coding Fc Gamma Receptor Cis-Regulatory Variant within the 1q23 Gene Cluster Is Associated with Plasmodium falciparum Infection in Children Residing in Burkina Faso

Antibodies play a crucial role in activating protective immunity against malaria by interacting with Fc-gamma receptors (FcγRs). Genetic variations in genes encoding FcγRs can affect immune cell responses to the parasite. In this study, our aim was to investigate whether non-coding variants that regulate FcγR expression could influence the prevalence of Plasmodium falciparum infection. Through bioinformatics approaches, we selected expression quantitative trait loci (eQTL) for FCGR2A, FCGR2B, FCGR2C, FCGR3A, and FCGR3B genes encoding FcγRs (FCGR), in whole blood. We prioritized two regulatory variants, rs2099684 and rs1771575, located in open genomic regions. These variants were identified using RegVar, ImmuNexUT, and transcription factor annotations specific to immune cells. In addition to these, we genotyped the coding variants FCGR2A/rs1801274 and FCGR2B/rs1050501 in 234 individuals from a malaria-endemic area in Burkina Faso. We conducted age and family-based analyses to evaluate associations with the prevalence of malarial infection in both children and adults. The analysis revealed that the regulatory rs1771575-CC genotype was predicted to influence FCGR2B/FCGR2C/FCGR3A transcripts in immune cells and was the sole variant associated with a higher prevalence of malarial infection in children. In conclusion, this study identifies the rs1771575 cis-regulatory variant affecting several FcγRs in myeloid and neutrophil cells and associates it with the inter-individual capacity of children living in Burkina Faso to control malarial infection.

Evolution of Plasmodium vivax and resistance patterns for infection based on Duffy genotype and phenotype

The Duffy protein, a transmembrane molecule, acts as a receptor for various chemokines and facilitates binding between reticulocytes and the Plasmodium Duffy antigen binding protein. Duffy expression is associated with the Duffy chemokine receptor antigen genotype on chromosome 1 and exhibits variation across different geographic regions. Traditionally, the Duffy negative genotype and phenotype have been described to confer a certain level of protection against infection and symptom development. However, recent data suggest a shift in this behavior, with significantly higher prevalence observed in individuals with Duffy negative genotype or phenotype. Given that malaria is an endemic vector-borne disease in regions of Asia, Africa, and Latin America, posing a substantial global burden of disease and prioritizing public and global health, identifying evolutionary changes in infection and resistance patterns holds great importance for the design of strategies and reevaluation of conventional interventions. Hence, the aim of this review was to analyze the evolution of Plasmodium vivax and infection resistance patterns based on Duffy genotype and phenotype. The distribution of genotypes, phenotypes, and polymorphisms of P. vivax ligands and erythrocyte receptors varies geographically, notably resistance patterns of this microorganism in individuals with Duffy negative genotype and phenotype have significantly changed compared to studies conducted 30 years ago. The prevalence of vivax malaria in individuals with a Duffy negative status can reach up to 100%. Consequently, prioritizing research on this topic is essential for public health.

Ancient DNA suggests anaemia and low bone mineral density as the cause for porotic hyperostosis in ancient individuals

Porotic hyperostosis (PH) is a disease that had high prevalence during the Neolithic. Several hypotheses have been suggested to explain the origin of the disease, such as an iron deficiency diet, low B12 intake, malaria caused by Plasmodium spp., low haemoglobin levels or low vitamin D levels. None of these hypotheses have been tested genetically. Here, I calculated different genetic scores to test each hypothesis. Additionally, I calculated a genetic score of bone mineral density as it is a phenotype that seems to be selected in ancient Europeans. I apply these genetic scores on 80 ancient samples, 33 with diagnosed PH. The results seem to suggest anaemia and low bone mineral density as the main cause for this disease. Additionally, Neolithic individuals show the lowest genetic risk score for bone mineral density of all other periods tested here, which may explain the highest prevalence of the porotic hyperostosis during this age.

Pathogenic Interleukin-10 Receptor Alpha Variants in Humans - Balancing Natural Selection and Clinical Implications

Balancing natural selection is a process by which genetic variants arise in populations that are beneficial to heterozygous carriers, but pathogenic when homozygous. We systematically investigated the prevalence, structural, and functional consequences of pathogenic IL10RA variants that are associated with monogenic inflammatory bowel disease. We identify 36 non-synonymous and non-sense variants in the IL10RA gene. Since the majority of these IL10RA variants have not been functionally characterized, we performed a systematic screening of their impact on STAT3 phosphorylation upon IL-10 stimulation. Based on the geographic accumulation of confirmed pathogenic IL10RA variants in East Asia and in Northeast China, the distribution of infectious disorders worldwide, and the functional evidence of IL-10 signaling in the pathogenesis, we identify Schistosoma japonicum infection as plausible selection pressure driving variation in IL10RA. Consistent with this is a partially augmented IL-10 response in peripheral blood mononuclear cells from heterozygous variant carriers. A parasite-driven heterozygote advantage through reduced IL-10 signaling has implications for health care utilization in regions with high allele frequencies and potentially indicates pathogen eradication strategies that target IL-10 signaling.

Risk score prediction model based on single nucleotide polymorphism for predicting malaria: a machine learning approach

Background

The malaria risk prediction is currently limited to using advanced statistical methods, such as time series and cluster analysis on epidemiological data. Nevertheless, machine learning models have been explored to study the complexity of malaria through blood smear images and environmental data. However, to the best of our knowledge, no study analyses the contribution of Single Nucleotide Polymorphisms (SNPs) to malaria using a machine learning model. More specifically, this study aims to quantify an individual's susceptibility to the development of malaria by using risk scores obtained from the cumulative effects of SNPs, known as weighted genetic risk scores (wGRS).

Results

We proposed an SNP-based feature extraction algorithm that incorporates the susceptibility information of an individual to malaria to generate the feature set. However, it can become computationally expensive for a machine learning model to learn from many SNPs. Therefore, we reduced the feature set by employing the Logistic Regression and Recursive Feature Elimination (LR-RFE) method to select SNPs that improve the efficacy of our model. Next, we calculated the wGRS of the selected feature set, which is used as the model's target variables. Moreover, to compare the performance of the wGRS-only model, we calculated and evaluated the combination of wGRS with genotype frequency (wGRS + GF). Finally, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), and Ridge regression algorithms are utilized to establish the machine learning models for malaria risk prediction.

Conclusions

Our proposed approach identified SNP rs334 as the most contributing feature with an importance score of 6.224 compared to the baseline, with an importance score of 1.1314. This is an important result as prior studies have proven that rs334 is a major genetic risk factor for malaria. The analysis and comparison of the three machine learning models demonstrated that LightGBM achieves the highest model performance with a Mean Absolute Error (MAE) score of 0.0373. Furthermore, based on wGRS + GF, all models performed significantly better than wGRS alone, in which LightGBM obtained the best performance (0.0033 MAE score).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04870-0.

An integrative skeletal and paleogenomic analysis of stature variation suggests relatively reduced health for early European farmers

Human culture, biology, and health were shaped dramatically by the onset of agriculture ∼12,000 y B.P. This shift is hypothesized to have resulted in increased individual fitness and population growth as evidenced by archaeological and population genomic data alongside a decline in physiological health as inferred from skeletal remains. Here, we consider osteological and ancient DNA data from the same prehistoric individuals to study human stature variation as a proxy for health across a transition to agriculture. Specifically, we compared “predicted” genetic contributions to height from paleogenomic data and “achieved” adult osteological height estimated from long bone measurements for 167 individuals across Europe spanning the Upper Paleolithic to Iron Age (∼38,000 to 2,400 B.P.). We found that individuals from the Neolithic were shorter than expected (given their individual polygenic height scores) by an average of −3.82 cm relative to individuals from the Upper Paleolithic and Mesolithic (P = 0.040) and −2.21 cm shorter relative to post-Neolithic individuals (P = 0.068), with osteological vs. expected stature steadily increasing across the Copper (+1.95 cm relative to the Neolithic), Bronze (+2.70 cm), and Iron (+3.27 cm) Ages. These results were attenuated when we additionally accounted for genome-wide genetic ancestry variation: for example, with Neolithic individuals −2.82 cm shorter than expected on average relative to pre-Neolithic individuals (P = 0.120). We also incorporated observations of paleopathological indicators of nonspecific stress that can persist from childhood to adulthood in skeletal remains into our model. Overall, our work highlights the potential of integrating disparate datasets to explore proxies of health in prehistory.

Leveraging Mann-Whitney U test on large-scale genetic variation data for analysing malaria genetic markers

Background

The malaria risk analysis of multiple populations is crucial and of great importance whilst compressing limitations. However, the exponential growth in diversity and accumulation of genetic variation data obtained from malaria-infected patients through Genome-Wide Association Studies opens up unprecedented opportunities to explore the significant differences between genetic markers (risk factors), particularly in the resistance or susceptibility of populations to malaria risk. Thus, this study proposes using statistical tests to analyse large-scale genetic variation data, comprising 20,854 samples from 11 populations within three continents: Africa, Oceania, and Asia.

Methods

Even though statistical tests have been utilized to conduct case–control studies since the 1950s to link risk factors to a particular disease, several challenges faced, including the choice of data (ordinal vs. non-ordinal) and test (parametric vs. non-parametric). This study overcomes these challenges by adopting the Mann–Whitney U test to analyse large-scale genetic variation data; to explore the statistical significance of markers between populations; and to further identify the highly differentiated markers.

Results

The findings of this study revealed a significant difference in the genetic markers between populations (p < 0.01) in all the case groups and most control groups. However, for the highly differentiated genetic markers, a significant difference (p < 0.01) was present for most genetic markers with varying p-values between the populations in the case and control groups. Moreover, several genetic markers were observed to have very significant differences (p < 0.001) across all populations, while others exist between certain specific populations. Also, several genetic markers have no significant differences between populations.

Conclusions

These findings further support that the genetic markers contribute differently between populations towards malaria resistance or susceptibility, thus showing differences in the likelihood of malaria infection. In addition, this study demonstrated the robustness of the Mann–Whitney U test in analysing genetic markers in large-scale genetic variation data, thereby indicating an alternative method to explore genetic markers in other complex diseases. The findings hold great promise for genetic markers analysis, and the pipeline emphasized in this study can fully be reproduced to analyse new data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04104-x.

Association of genetic variations in ACE2, TIRAP and factor X with outcomes in COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can manifest with varying disease severity and mortality. Genetic predisposition influences the clinical course of infectious diseases. We investigated whether genetic polymorphisms in candidate genes ACE2, TIRAP, and factor X are associated with clinical outcomes in COVID-19.

METHODS

We conducted a single-centre retrospective cohort study. All patients who visited the emergency department with SARS-CoV-2 infection proven by polymerase chain reaction were included. Single nucleotide polymorphisms in ACE2 (rs2285666), TIRAP (rs8177374) and factor X (rs3211783) were assessed. The outcomes were mortality, respiratory failure and venous thromboembolism. Respiratory failure was defined as the necessity of >5 litres/minute oxygen, high flow nasal oxygen suppletion or mechanical ventilation.

RESULTS

Between March and April 2020, 116 patients (35% female, median age 65 [inter quartile range 55-75] years) were included and treated according to the then applicable guidelines. Sixteen patients (14%) died, 44 patients (38%) had respiratory failure of whom 23 required endotracheal intubation for mechanical ventilation, and 20 patients (17%) developed venous thromboembolism. The percentage of TIRAP polymorphism carriers in the survivor group was 28% as compared to 0% in the non-survivor group (p = 0.01, Bonferroni corrected p = 0.02). Genotype distribution of ACE2 and factor X did not differ between survivors and non-survivors.

CONCLUSION

This study shows that carriage of TIRAP polymorphism rs8177374 could be associated with a significantly lower mortality in COVID-19. This TIRAP polymorphism may be an important predictor in the outcome of COVID-19.

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.

Malaria in Europe: A Historical Perspective

Endemic malaria, which claimed 229 million new cases and 409,000 deaths in 2019 mainly in Africa, was eradicated from Europe by the mid-20th century. Historical descriptions of intermittent tertian and quartan fever reported in texts of Hippocrates in Greece and Celsus in Italy suggest malaria. A few paleomicrobiology investigations have confirmed the presence of malarial parasite Plasmodium falciparum in 1st, 2nd, and 5th century infected individuals in diverse regions of Italy, and Plasmodium sp. later in Bavaria. The causative Plasmodium pathogens, discovered in the 19th century in Algeria, were controversially used as therapeutic agents in the European pharmacopeia more than two centuries after effective quinine-based treatments had been introduced in Europe. How Europe managed to eradicate malaria and what the history of malaria was in Europe are of medical interest, and this review traces research pathways for a renewed understanding of malaria eradication in Europe through combined historical and paleomicrobiological investigations.

How Genetics Might Explain the Unusual Link Between Malaria and COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated coronavirus disease 2019 (COVID-19) pandemic has been the subject of a large number of studies in recent times. Here, starting from the evidence that in Italy, the areas with the lowest number of COVID-19 cases were those with the highest incidence of malaria in the early 1900's, we explore possible inverse relationships between malaria and COVID-19. Indeed, some genetic variants, which have been demonstrated to give an advantage against malaria, can also play a role in the incidence and severity of SARS-CoV-2 infections (e.g., the ACE2 receptor). To verify this scientific hypothesis, we here use public data from whole-genome sequencing (WGS) experiments to extrapolate the genetic information of 46 world populations with matched COVID-19 data. In particular, we focus on 47 genes, including ACE2 and genes which have previously been reported to play a role in malaria. Only common variants (>5%) in at least 30% of the selected populations were considered, and, for this subset, we correlate the intra-population allele frequency with the COVID-19 data (cases/million inhabitants), eventually pinpointing meaningful variants in 6 genes. This study allows us to distinguish between positive and negative correlations, i.e., variants whose frequency significantly increases with increasing or decreasing COVID-19 cases. Finally, we discuss the possible molecular mechanisms associated with these variants and advance potential therapeutic options, which may help fight and/or prevent COVID-19.

Three Signatures of Adaptive Polymorphism Exemplified by Malaria-Associated Genes

Malaria has been one of the strongest selective pressures on our species. Many of the best-characterized cases of adaptive evolution in humans are in genes tied to malaria resistance. However, the complex evolutionary patterns at these genes are poorly captured by standard scans for nonneutral evolution. Here, we present three new statistical tests for selection based on population genetic patterns that are observed more than once among key malaria resistance loci. We assess these tests using forward-time evolutionary simulations and apply them to global whole-genome sequencing data from humans, and thus we show that they are effective at distinguishing selection from neutrality. Each test captures a distinct evolutionary pattern, here called Divergent Haplotypes, Repeated Shifts, and Arrested Sweeps, associated with a particular period of human prehistory. We clarify the selective signatures at known malaria-relevant genes and identify additional genes showing similar adaptive evolutionary patterns. Among our top outliers, we see a particular enrichment for genes involved in erythropoiesis and for genes previously associated with malaria resistance, consistent with a major role for malaria in shaping these patterns of genetic diversity. Polymorphisms at these genes are likely to impact resistance to malaria infection and contribute to ongoing host-parasite coevolutionary dynamics.

Ancestry-Specific Analyses Reveal Differential Demographic Histories and Opposite Selective Pressures in Modern South Asian Populations

Genetic variation in contemporary South Asian populations follows a northwest to southeast decreasing cline of shared West Eurasian ancestry. A growing body of ancient DNA evidence is being used to build increasingly more realistic models of demographic changes in the last few thousand years. Through high-quality modern genomes, these models can be tested for gene and genome level deviations. Using local ancestry deconvolution and masking, we reconstructed population-specific surrogates of the two main ancestral components for more than 500 samples from 25 South Asian populations and showed our approach to be robust via coalescent simulations.

Our f3 and f4 statistics–based estimates reveal that the reconstructed haplotypes are good proxies for the source populations that admixed in the area and point to complex interpopulation relationships within the West Eurasian component, compatible with multiple waves of arrival, as opposed to a simpler one wave scenario. Our approach also provides reliable local haplotypes for future downstream analyses. As one such example, the local ancestry deconvolution in South Asians reveals opposite selective pressures on two pigmentation genes (SLC45A2 and SLC24A5) that are common or fixed in West Eurasians, suggesting post-admixture purifying and positive selection signals, respectively.

Positive selection in Europeans and East-Asians at the ABCA12 gene

Natural selection acts on genetic variants by increasing the frequency of alleles responsible for a cellular function that is favorable in a certain environment. In a previous genome-wide scan for positive selection in contemporary humans, we identified a signal of positive selection in European and Asians at the genetic variant rs10180970. The variant is located in the second intron of the ABCA12 gene, which is implicated in the lipid barrier formation and down-regulated by UVB radiation. We studied the signal of selection in the genomic region surrounding rs10180970 in a larger dataset that includes DNA sequences from ancient samples. We also investigated the functional consequences of gene expression of the alleles of rs10180970 and another genetic variant in its proximity in healthy volunteers exposed to similar UV radiation. We confirmed the selection signal and refine its location that extends over 35 kb and includes the first intron, the first two exons and the transcription starting site of ABCA12. We found no obvious effect of rs10180970 alleles on ABCA12 gene expression. We reconstructed the trajectory of the T allele over the last 80,000 years to discover that it was specific to H. sapiens and present in non-Africans 45,000 years ago.

Genome-wide data from the Bubi of Bioko Island clarifies the Atlantic fringe of the Bantu dispersal

BACKGROUND

Bioko is one of the few islands that exist around Africa, the most genetically diverse continent on the planet. The native Bantu-speaking inhabitants of Bioko, the Bubi, are believed to have colonized the island about 2000 years ago. Here, we sequenced the genome of thirteen Bubi individuals at high coverage and analysed their sequences in comparison to mainland populations from the Gulf of Guinea.

RESULTS

We found that, genetically, the closest mainland population to the Bubi are Bantu-speaking groups from Angola instead the geographically closer groups from Cameroon. The Bubi possess a lower proportion of rainforest hunter-gatherer (RHG) ancestry than most other Bantu-speaking groups. However, their RHG component most likely came from the same source and could have reached them by gene flow from the mainland after island settlement. By studying identity by descent (IBD) genomic blocks and runs of homozygosity (ROHs), we found evidence for a significant level of genetic isolation among the Bubi, isolation that can be attributed to the island effect. Additionally, as this population is known to have one of the highest malaria incidence rates in the world we analysed their genome for malaria-resistant alleles. However, we were unable to detect any specific selective sweeps related to this disease.

CONCLUSIONS

By describing their dispersal to the Atlantic islands, the genomic characterization of the Bubi contributes to the understanding of the margins of the massive Bantu migration that shaped all Sub-Saharan African populations.

Genetic signatures of gene flow and malaria-driven natural selection in sub-Saharan populations of the "endemic Burkitt Lymphoma belt"

Populations in sub-Saharan Africa have historically been exposed to intense selection from chronic infection with falciparum malaria. Interestingly, populations with the highest malaria intensity can be identified by the increased occurrence of endemic Burkitt Lymphoma (eBL), a pediatric cancer that affects populations with intense malaria exposure, in the so called "eBL belt" in sub-Saharan Africa. However, the effects of intense malaria exposure and sub-Saharan populations' genetic histories remain poorly explored. To determine if historical migrations and intense malaria exposure have shaped the genetic composition of the eBL belt populations, we genotyped ~4.3 million SNPs in 1,708 individuals from Ghana and Northern Uganda, located on opposite sides of eBL belt and with ≥ 7 months/year of intense malaria exposure and published evidence of high incidence of BL. Among 35 Ghanaian tribes, we showed a predominantly West-Central African ancestry and genomic footprints of gene flow from Gambian and East African populations. In Uganda, the North West population showed a predominantly Nilotic ancestry, and the North Central population was a mixture of Nilotic and Southern Bantu ancestry, while the Southwest Ugandan population showed a predominant Southern Bantu ancestry. Our results support the hypothesis of diverse ancestral origins of the Ugandan, Kenyan and Tanzanian Great Lakes African populations, reflecting a confluence of Nilotic, Cushitic and Bantu migrations in the last 3000 years. Natural selection analyses suggest, for the first time, a strong positive selection signal in the ATP2B4 gene (rs10900588) in Northern Ugandan populations. These findings provide important baseline genomic data to facilitate disease association studies, including of eBL, in eBL belt populations.

Searching for signals of recent natural selection in genes of the innate immune response - ancient DNA study

The last decade has seen sharp progress in the field of human evolutionary genetics and a great amount of genetic evidence of natural selection has been provided so far. Since host-pathogen co-evolution is difficult to trace due to the polygenic nature of human susceptibility to microbial diseases, of particular interest is any signal of natural selection in response to the strong selective pressure exerted by pathogens. Analysis of ancient DNA allows for the direct insight into changes of a gene pool content over time and enables monitoring allele frequency fluctuations. Among pathogenic agents, mycobacteria are proved to have remained in an intimate, long-lasting relation with humans, reflected by the current high level of host resistance. Therefore, we aimed to investigate the prevalence of several polymorphisms within innate immune response genes related to susceptibility to mycobacterial diseases (in SLC11A1, MBL2, TLR2, P2RX7, IL10, TNFA) in time series data from North and East Poland (1st-18th century AD, n = 207). The comparison of allele frequencies over time revealed a predominant role of genetic drift in shaping past gene pool of small, probably isolated groups, which was explained by the high level of population differentiation and limited gene flow. However, the trajectory of frequency fluctuations of two SNPs suggested the possibility of their non-neutral evolution and the results of applied forward simulations further strengthened the hypothesis of natural selection acting on those loci. However, we observed an unusual excess of homozygosity in the profile of several SNPs, which pinpoints to the necessity of further research on temporally and spatially diverse samples to support our inference on non-stochastic evolution, ideally employing pathway-based approaches. Nevertheless, our study confirms that time series data could help to decipher very recent human adaptation to life-threatening pathogens and assisting demographic events.

Harnessing ancient genomes to study the history of human adaptation

The past several years have witnessed an explosion of successful ancient human genome-sequencing projects, with genomic-scale ancient DNA data sets now available for more than 1,100 ancient human and archaic hominin (for example, Neandertal) individuals. Recent 'evolution in action' analyses have started using these data sets to identify and track the spatiotemporal trajectories of genetic variants associated with human adaptations to novel and changing environments, agricultural lifestyles, and introduced or co-evolving pathogens. Together with evidence of adaptive introgression of genetic variants from archaic hominins to humans and emerging ancient genome data sets for domesticated animals and plants, these studies provide novel insights into human evolution and the evolutionary consequences of human behaviour that go well beyond those that can be obtained from modern genomic data or the fossil and archaeological records alone.