McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks.

Haplotype networks are graphs used to represent evolutionary relationships between a set of taxa and are characterized by intuitiveness in analyzing genealogical relationships of closely related genomes. We here propose a novel algorithm termed McAN that considers mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time when constructing haplotype network. We show that McAN is two orders of magnitude faster than state-of-the-art algorithms without losing accuracy, making it suitable for analysis of a large number of sequences. Based on our algorithm, we developed an online web server and offline tool for haplotype network construction, community lineage determination, and interactive network visualization. We demonstrate that McAN is highly suitable for analyzing and visualizing massive genomic data and is helpful to enhance the understanding of genome evolution. Availability: Source code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. Web server is available at https://ngdc.cncb.ac.cn/bit/hapnet/. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/. Contact: songshh@big.ac.cn (Song S), zhaowm@big.ac.cn (Zhao W), baoym@big.ac.cn (Bao Y), zhangzhang@big.ac.cn (Zhang Z), ybxue@big.ac.cn (Xue Y).

Towards evolutionary predictions: Current promises and challenges.

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Fifty Years of Research on Camelids and the Contribution of Genetics and Genomics: A Scientometrics Evaluation

The population and importance of camels in human life have improved in recent years. As genetics and genomics are becoming a more comprehensive section of life sciences, studying genetic/genomic aspects of the camelid nutrition, milk production, reproduction, immunity, disease and racing ability has become common in recent years. This study was conducted based on text mining and scientometrics techniques. To employ relevant information from Web of Science (WoS), a search strategy was developed to retrieve the "genetics or genomics” and words/phrases related to "camelids”. The statistical population of this study included 3830 publications over a period of 50 years (1971–2020). A total of 3830 publications were retrieved that included 3269 research articles (85.35% of the publications) and 224 review articles (5.85% of the publications). The most frequent subject groups were "Veterinary Sciences” including 862 publications. In total, articles on camelid genomics were published in 1345 journals. Moreover, 127 countries contributed to these 3830 publications, with the USA being the leading country both in number of publications and international collaboration. During the 1971–2010 time period, the phrases "MERS-CoV” and "coronavirus” did not exist in the literature at all, while in the last decade, with 140 and 63 times (5.36% and 2.41%, respectively), they were the most frequent keywords. In general, the most important topics studied from the perspective of camelid genomics have been population genetics and pathogens and their diagnosis, as well as camelid immunity. Future studies should pay special attention to the specificity of camelid genomics for hosting the coronavirus. Furthermore, the special structure of humoral immunity in camels makes this section attractive in immunogenetics research. © 2023, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering. All rights reserved.

The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions.

The COVID-19 pandemic has revealed the need for the increased integration of modelling and data analysis to public health, experimental, and clinical studies. Throughout the first two years of the pandemic, there has been a concerted effort to improve our understanding of the within-host immune response to the SARS-CoV-2 virus to provide better predictions of COVID-19 severity, treatment and vaccine development questions, and insights into viral evolution and the impacts of variants on immunopathology. Here we provide perspectives on what has been accomplished using quantitative methods, including predictive modelling, population genetics, machine learning, and dimensionality reduction techniques, in the first 26 months of the COVID-19 pandemic approaches, and where we go from here to improve our responses to this and future pandemics.

Special Collection: Highlights of Medical, Urban and Veterinary Entomology. Highlights in Medical Entomology, 2021.

Life remained far from normal as we completed the first year of the Covid-19 pandemic and entered a second year. Despite the challenges faced worldwide, together we continue to move the field of Medical Entomology forward. Here, I reflect on parallels between control of Covid-19 and vector-borne disease control, discuss the advantages and caveats of using new genotyping technologies for the study of invasive species, and proceed to highlight papers that were published between 2020 and 2021 with a focus on those related to mosquito surveillance and population genetics of mosquito vectors.

Low disease incidence and cone bagging in Picea abies are associated with low genotypic diversity in Thekopsora areolata

Thekopsora areolata infects pistillate cones of Picea spp. with monokaryotic basidiospores in the spring. Receptive monokaryotic hyphae in the cones are fertilized by monokaryotic spermatia in the summer, and dikaryotic aecia are produced in cones in late summer. Infected cones produce no fertile seeds, meaning the disease causes large reductions in seed production. To understand the seasonal variation of T. areolata genotypic diversity, 548 aecia from 55 infected cones were sampled from multiple seed orchards in 2015, 2019 and 2020. Cone bagging experiments were performed during two seasons to investigate the sexual reproduction of T. areolata. In addition to the published simple‐sequence repeat (SSR) markers, we developed 10 new polymorphic SSR markers to improve the resolution of population genetic analysis. Aecia were genotyped with 18 SSR markers in total. In 2015, when disease incidence was high in the seed orchards, the T. areolata populations had high genotypic diversity (H = 4.69). In 2019 and 2020, when disease incidence was low, the T. areolata populations had lower genotypic diversity (H = 3.88 and 3.85) and several cones were dominated by a single multilocus genotype. The genotypic diversity of T. areolata in a recently established seed orchard was exceptionally low (H = 2.01). Seven bagged cones that were infected produced either aecial primordia or aecia with lower diversity than exposed cones. The results indicate that cross‐fertilization is important for sexual reproduction and aecia formation of T. areolata, and genotypic diversity of T. areolata increased with higher disease prevalence. [ FROM AUTHOR] Copyright of Plant Pathology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Evidence of Genetic Connectivity among Lyle’s Flying Fox Populations in Thailand for Wildlife Management and One Health Framework

Bats are important reservoir hosts of emerging viruses. Recent viral outbreaks and pandemics have resulted in an increased research focus on the genetic diversity, population structure, and distribution of bat species. Lyle’s flying fox (Pteropus lylei) is widely distributed throughout central Thailand, with most colonies congregating in temples within proximity to humans. A lack of knowledge regarding the genetic connectivity among different colonies hinders the investigation of zoonotic disease epidemiology and wildlife management. In this study, we hypothesized that genetic material may be exchanged between Lyle’s flying fox colonies that live in proximity. We assessed the mitochondrial displacement loop and cytochrome b nucleotide sequences of samples collected from 94 individuals from ten colonies across different roosting sites and detected limited genetic differentiation but increased nucleotide divergence within colonies. This suggests that genetic connectivity among Lyle’s flying fox colonies has experienced frequent and recent gene flow. These findings indicate that this species has maintained demographic equilibrium in a stable population, with a slight expansion event in certain populations. These data provide insights into the dynamics of bat populations, and the genetic knowledge gained presents opportunities for the improved monitoring of bat population structure.

Association between single nucleotide polymorphism of human angiotensin-converting enzyme 2 gene locus and clinical severity of COVID-19

BackgroundCoronavirus disease 2019 (COVID-19) is a devastating pandemic-causing disease with a variable severity among populations. Genetic studies have pinpointed angiotensin-converting enzyme 2 (ACE2), a key enzyme for viral entry, for its possible linkage to the disease progression. The present study aimed to investigate the potential association between single nucleotide polymorphisms (SNPs) of human ACE2 gene with the severity and outcomes of COVID-19 for better patient management. MethodsIn this observational cross-sectional study, COVID-19 confirmed patients were classified into moderate and severe cases according to the “Ain Shams University Hospitals Pocket Guide for COVID-19 Diagnosis.” Genetic analysis of ACE2 SNP rs2048683 was carried out using a TaqMan assay with the real-time polymerase chain reaction (PCR) technique.ResultsAmong 90 confirmed COVID-19 patients, 78.9% (71/90) were classified as severe, and 21.1% (19/90) were classified as moderate. Laboratory biomarkers were significantly (P = 0.000) higher in the severe group than in the moderate group. Similarly, associated comorbidities such as hypertension were significant (P = 0.000) in the severe group, whereas asthma and deep venous thrombosis were significant in the moderate group (P = 0.007 and 0.006, respectively). Elevated serum ferritin level (odds ratio (OR) 162.589, 95% confidence interval (CI) 8.108–3260.293) and ACE2 rs2048683 genotype GG/G (OR 5.852, 95% CI 1.586–21.591) were both considered independent risk factors for severe disease.ConclusionThe findings of the present study provide preliminary evidence of an association between ACE2 rs2048683 SNPs and COVID-19 severity in the Egyptian population, which may inform the need for targeted management.

Evolutionary dynamics of the severe acute respiratory syndrome coronavirus 2 genomes.

The coronavirus disease 2019 (COVID-19) pandemic has caused immense losses in human lives and the global economy and posed significant challenges for global public health. As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has evolved, thousands of single nucleotide variants (SNVs) have been identified across the viral genome. The roles of individual SNVs in the zoonotic origin, evolution, and transmission of SARS-CoV-2 have become the focus of many studies. This review summarizes recent comparative genomic analyses of SARS-CoV-2 and related coronaviruses (SC2r-CoVs) found in non-human animals, including delineation of SARS-CoV-2 lineages based on characteristic SNVs. We also discuss the current understanding of receptor-binding domain (RBD) evolution and characteristic mutations in variants of concern (VOCs) of SARS-CoV-2, as well as possible co-evolution between RBD and its receptor, angiotensin-converting enzyme 2 (ACE2). We propose that the interplay between SARS-CoV-2 and host RNA editing mechanisms might have partially resulted in the bias in nucleotide changes during SARS-CoV-2 evolution. Finally, we outline some current challenges, including difficulty in deciphering the complicated relationship between viral pathogenicity and infectivity of different variants, and monitoring transmission of SARS-CoV-2 between humans and animals as the pandemic progresses.

edna2021: The fourth annual meeting of The eDNA Society “Species distributions, and beyond”

The eDNA Society was founded in Japan in 2018 to develop eDNA science as a discipline that contributes to the human well‐being and the sustainable use of ecosystems. Since then, the society has expanded attracting a wide variety of people from international universities, research institutes, consultant companies, and local/national governments. Here we report edna2021, the fourth annual meeting of The eDNA Society, which was held mainly online on November 20–21, 2021. We had c.a. 500 participants in total, from at least 15 countries. In the meeting, we discussed not only the technical aspects of environmental DNA but also its potential for various applications including its combinations with environmental RNA, sediment core samples, population genetic analyses, etc.

Current Status and Potential of Biofortification to Enhance Crop Nutritional Quality: An Overview

Around 2 billion people are suffering from chronic malnutrition or “hidden hunger”, which is the result of many diseases and disorders, including cognitive degeneration, stunting growth, and mortality. Thus, biofortification of staple food crops enriched with micronutrients is a more sustainable option for providing nutritional supplements and managing malnutrition in a society. Since 2001, when the concept of biofortification came to light, different research activities have been carried out, like the development of target populations, breeding or genetic engineering, and the release of biofortified cultivars, in addition to conducting nutritional efficacy trials and delivery plan development. Although, being a cost-effective intervention, it still faces many challenges, like easy accessibility of biofortified cultivars, stakeholders’ acceptance, and the availability of biofortified germplasm in the public domain, which varies from region to region. Hence, this review is focused on the recent potential, efforts made to crop biofortification, impacts analysis on human health, cost-effectiveness, and future perspectives to further strengthen biofortification programs. Through regular interventions of sustainable techniques and methodologies, biofortification holds huge potential to solve the malnutrition problem through regular interventions of nutrient-enriched staple food options for billions of people globally.

Temporal data series and logistic models reveal the dynamics of SARS-CoV-2 spike protein D614G variant in the COVID-19 pandemic

The COVID-19 pandemic is caused by the worldwide spread of the RNA virus SARS-CoV-2. Because of its mutational rate, wide geographical distribution, and host response variance this coronavirus is currently evolving into an array of strains with increasing genetic diversity. Most variants apparently have neutral effects for disease spread and symptom severity. However, in the viral spike protein, which is responsible for host cell attachment and invasion, the D614G variant, containing the amino acid substitution D to G in position 614, was suggested to increase viral infection capability. Here we propose a novel method to test the epidemiological impact of emergence of a new variant, by a combination of epidemiological curves (for new cases) and the temporal variation of relative frequencies of the variants through a logistic regression model. We applied our method to temporal distributions of SARS-CoV-2 D614 or G614, in two geographic areas: USA (East Coast versus West Coast) and Europe-Asia (East Countries versus West Countries). Our analysis shows that the D614G prevalence and the growth rates of COVID-19 epidemic data curves are correlated at the early stages and not correlated at the late stages, in both the USA andEurope-Asia scenarios. These results show that logistic models can reveal the potential selective advantage of D614G, which can explain, at least in part, the impact of this variant on COVID-19 epidemiology.

Microorganisms as Shapers of Human Civilization, from Pandemics to Even Our Genomes: Villains or Friends? A Historical Approach.

Universal history is characterized by continuous evolution, in which civilizations are born and die. This evolution is associated with multiple factors, among which the role of microorganisms is often overlooked. Viruses and bacteria have written or decisively contributed to terrible episodes of history, such as the Black Death in 14th century Europe, the annihilation of pre-Columbian American civilizations, and pandemics such as the 1918 Spanish flu or the current COVID-19 pandemic caused by the coronavirus SARS-CoV-2. Nevertheless, it is clear that we could not live in a world without these tiny beings. Endogenous retroviruses have been key to our evolution and for the regulation of gene expression, and the gut microbiota helps us digest compounds that we could not otherwise process. In addition, we have used microorganisms to preserve or prepare food for millennia and more recently to obtain drugs such as antibiotics or to develop recombinant DNA technologies. Due to the enormous importance of microorganisms for our survival, they have significantly influenced the population genetics of different human groups. This paper will review the role of microorganisms as "villains" who have been responsible for tremendous mortality throughout history but also as "friends" who help us survive and evolve.

Interaction between M. tuberculosis Lineage and Human Genetic Variants Reveals Novel Pathway Associations with Severity of TB.

Tuberculosis (TB) remains a major public health threat globally, especially in sub-Saharan Africa. Both human and Mycobacterium tuberculosis (MTBC) genetic variation affect TB outcomes, but few studies have examined if and how the two genomes interact to affect disease. We hypothesize that long-term coexistence between human genomes and MTBC lineages modulates disease to affect its severity. We examined this hypothesis in our TB household contact study in Kampala, Uganda, in which we identified three MTBC lineages, of which one, L4.6-Uganda, is clearly derived and hence recent. We quantified TB severity using the Bandim TBscore and examined the interaction between MTBC lineage and human single-nucleotide polymorphisms (SNPs) genome-wide, in two independent cohorts of TB cases (n = 149 and n = 127). We found a significant interaction between an SNP in PPIAP2 and the Uganda lineage (combined p = 4 × 10-8). PPIAP2 is a pseudogene that is highly expressed in immune cells. Pathway and eQTL analyses indicated potential roles between coevolving SNPs and cellular replication and metabolism as well as platelet aggregation and coagulation. This finding provides further evidence that host-pathogen interactions affect clinical presentation differently than host and pathogen genetic variation independently, and that human-MTBC coevolution is likely to explain patterns of disease severity.

Poking COVID-19: Insights on Genomic Constraints among Immune-Related Genes between Qatari and Italian Populations.

Host genomic information, specifically genomic variations, may characterize susceptibility to disease and identify people with a higher risk of harm, leading to better targeting of care and vaccination. Italy was the epicentre for the spread of COVID-19 in Europe, the first country to go into a national lockdown and has one of the highest COVID-19 associated mortality rates. Qatar, on the other hand has a very low mortality rate. In this study, we compared whole-genome sequencing data of 14398 adults and Qatari-national to 925 Italian individuals. We also included in the comparison whole-exome sequence data from 189 Italian laboratory-confirmed COVID-19 cases. We focused our study on a curated list of 3619 candidate genes involved in innate immunity and host-pathogen interaction. Two population-gene metric scores, the Delta Singleton-Cohort variant score (DSC) and Sum Singleton-Cohort variant score (SSC), were applied to estimate the presence of selective constraints in the Qatari population and in the Italian cohorts. Results based on DSC and SSC metrics demonstrated a different selective pressure on three genes (MUC5AC, ABCA7, FLNA) between Qatari and Italian populations. This study highlighted the genetic differences between Qatari and Italian populations and identified a subset of genes involved in innate immunity and host-pathogen interaction.

Binding affinities of 438 HLA proteins to complete proteomes of seven pandemic viruses and distributions of strongest and weakest HLA peptide binders in populations worldwide.

We report detailed peptide-binding affinities between 438 HLA Class I and Class II proteins and complete proteomes of seven pandemic human viruses, including coronaviruses, influenza viruses and HIV-1. We contrast these affinities with HLA allele frequencies across hundreds of human populations worldwide. Statistical modelling shows that peptide-binding affinities classified into four distinct categories depend on the HLA locus but that the type of virus is only a weak predictor, except in the case of HIV-1. Among the strong HLA binders (IC50 ≤ 50), we uncovered 16 alleles (the top ones being A*02:02, B*15:03 and DRB1*01:02) binding more than 1% of peptides derived from all viruses, 9 (top ones including HLA-A*68:01, B*15:25, C*03:02 and DRB1*07:01) binding all viruses except HIV-1, and 15 (top ones A*02:01 and C*14:02) only binding coronaviruses. The frequencies of strongest and weakest HLA peptide binders differ significantly among populations from different geographic regions. In particular, Indigenous peoples of America show both higher frequencies of strongest and lower frequencies of weakest HLA binders. As many HLA proteins are found to be strong binders of peptides derived from distinct viral families, and are hence promiscuous (or generalist), we discuss this result in relation to possible signatures of natural selection on HLA promiscuous alleles due to past pathogenic infections. Our findings are highly relevant for both evolutionary genetics and the development of vaccine therapies. However they should not lead to forget that individual resistance and vulnerability to diseases go beyond the sole HLA allelic affinity and depend on multiple, complex and often unknown biological, environmental and other variables.

Genomic Diversity of Azole-Resistant Aspergillus fumigatus in the United States.

Azole resistance in pathogenic Aspergillus fumigatus has become a global public health issue threatening the use of medical azoles. The environmentally occurring resistance mutations, TR34/L98H (TR34) and TR46/Y121F/T289A (TR46), are widespread across multiple continents and emerging in the United States. We used whole-genome single nucleotide polymorphism (SNP) analysis on 179 nationally represented clinical and environmental A. fumigatus genomes from the United States along with 18 non-U.S. genomes to evaluate the genetic diversity and foundation of the emergence of azole resistance in the United States. We demonstrated the presence of clades of A. fumigatus isolates: clade A (17%) comprised a global collection of clinical and environmental azole-resistant strains, including all strains with the TR34/L98H allele from India, The Netherlands, the United Kingdom, and the United States, and clade B (83%) consisted of isolates without this marker mainly from the United States. The TR34/L98H polymorphism was shared among azole-resistant A. fumigatus strains from India, The Netherlands, the United Kingdom, and the United States, suggesting the common origin of this resistance mechanism. Six percent of azole-resistant A. fumigatus isolates from the United States with the TR34 resistance marker had a mixture of clade A and clade B alleles, suggestive of recombination. Additionally, the presence of equal proportions of both mating types further suggests the ongoing presence of recombination. This study demonstrates the genetic background for the emergence of azole resistance in the United States, supporting a single introduction and subsequent propagation, possibly through recombination of environmentally driven resistance mutations. IMPORTANCE Aspergillus fumigatus is one of the most common causes of invasive mold infections in patients with immune deficiencies and has also been reported in patients with severe influenza and severe acute respiratory syndrome coronavirus 2 (SARs-CoV-2). Triazole drugs are the first line of therapy for this infection; however, their efficacy has been compromised by the emergence of azole resistance in A. fumigatus, which was proposed to be selected for by exposure to azole fungicides in the environment [P. E. Verweij, E. Snelders, G. H. J. Kema, E. Mellado, et al., Lancet Infect Dis 9:789-795, 2009, https://doi.org/10.1016/S1473-3099(09)70265-8]. Isolates with environmentally driven resistance mutations, TR34/L98H (TR34) and TR46/Y121F/T289A (TR46), have been reported worldwide. Here, we used genomic analysis of a large sample of resistant and susceptible A. fumigatus isolates to demonstrate a single introduction of TR34 in the United States and suggest its ability to spread into the susceptible population is through recombination between resistant and susceptible isolates.

Association of Vitamin D, Zinc and Selenium Related Genetic Variants With COVID-19 Disease Severity.

Background: COVID-19 pandemic has proved to be an unrelenting health threat for more than a year now. The emerging amount of data indicates that vitamin D, zinc and selenium could be important for clinical presentation of COVID-19. Here, we investigated association of genetic variants related to the altered level and bioavailability of vitamin D, zinc and selenium with clinical severity of COVID-19. Methods: We analyzed variants in genes significant for the status of vitamin D (DHCR7/NADSYN1 rs12785878, GC rs2282679, CYP2R1 rs10741657, and VDR rs2228570), zinc (PPCDC rs2120019) and selenium (DMGDH rs17823744) in 120 Serbian adult and pediatric COVID-19 patients using allelic discrimination. Furthermore, we carried out comparative population genetic analysis among European and other worldwide populations to investigate variation in allelic frequencies of selected variants. Results: Study showed that DHCR7/NADSYN rs12785878 and CYP2R1 rs10741657 variants were associated with severe COVID-19 in adults (p = 0.03, p = 0.017, respectively); carriers of DHCR7/NADSYN TG+GG and CYP2R1 GG genotypes had 0.21 and 5.9 the odds for developing severe disease, OR 0.21 (0.05-0.9) and OR 5.9 (1.4-25.2), respectively. There were no associations between selected genetic variants and disease severity in pediatric patients. Comparative population genetic analysis revealed that Serbian population had the lowest frequency of CYP2R1 rs10741657 G allele compared to other non-Finish Europeans (0.58 compared to 0.69 and 0.66 in Spanish and Italian population, respectively), suggesting that other populations should also investigate the relationship of CYP2R1 variant and the COVID-19 disease course. Conclusion: The results of the study indicated that vitamin D related genetic variants were implicated in severe COVID-19 in adults. This could direct prevention strategies based on population specific nutrigenetic profiles.

Design of a FAIR digital data health infrastructure in Africa for COVID-19 reporting and research.

The limited volume of COVID-19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS-CoV-2 mutations. The Virus Outbreak Data Network (VODAN)-Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID-19, producing these as human- and machine-readable data objects in a distributed architecture of locally governed, linked, human- and machine-readable data. This architecture supports analytics at the point of care and-through data visiting, across facilities-for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.