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.

Disentangling Signatures of Selection Before and After European Colonization in Latin Americans.

Throughout human evolutionary history, large-scale migrations have led to intermixing (i.e., admixture) between previously separated human groups. Although classical and recent work have shown that studying admixture can yield novel historical insights, the extent to which this process contributed to adaptation remains underexplored. Here, we introduce a novel statistical model, specific to admixed populations, that identifies loci under selection while determining whether the selection likely occurred post-admixture or prior to admixture in one of the ancestral source populations. Through extensive simulations, we show that this method is able to detect selection, even in recently formed admixed populations, and to accurately differentiate between selection occurring in the ancestral or admixed population. We apply this method to genome-wide SNP data of ∼4,000 individuals in five admixed Latin American cohorts from Brazil, Chile, Colombia, Mexico, and Peru. Our approach replicates previous reports of selection in the human leukocyte antigen region that are consistent with selection post-admixture. We also report novel signals of selection in genomic regions spanning 47 genes, reinforcing many of these signals with an alternative, commonly used local-ancestry-inference approach. These signals include several genes involved in immunity, which may reflect responses to endemic pathogens of the Americas and to the challenge of infectious disease brought by European contact. In addition, some of the strongest signals inferred to be under selection in the Native American ancestral groups of modern Latin Americans overlap with genes implicated in energy metabolism phenotypes, plausibly reflecting adaptations to novel dietary sources available in the Americas.

TLR9 signalling inhibits Plasmodium liver infection by macrophage activation.

Recognition of pathogen-associated molecular patterns (PAMPs) through Toll-like receptors (TLRs) plays a pivotal role in first-line pathogen defense. TLRs are also likely triggered during a Plasmodium infection in vivo by parasite-derived components. However, the contribution of innate responses to liver infection and to the subsequent clinical outcome of a blood infection is not well understood. To assess the potential effects of enhanced TLR-signalling on Plasmodium infection, we systematically examined the effect of agonist-primed immune responses to sporozoite inoculation in the P. berghei/C57Bl/6 murine malaria model. We could identify distinct stage-specific effects on the course of infection after stimulation with two out of four TLR-ligands tested. Priming with a TLR9 agonist induced killing of pre-erythrocytic stages in the liver that depended on macrophages and the expression of inducible nitric oxide synthase (iNOS). These factors have previously not been recognized as antigen-independent effector mechanisms against Plasmodium liver stages. Priming with TLR4 and -9 agonists also translated into blood stage-specific protection against experimental cerebral malaria (ECM). These insights are relevant to the activation of TLR signalling pathways by adjuvant systems of antimalaria vaccine strategies. The protective role of TLR4-activation against ECM might also explain some unexpected clinical effects observed with pre-erythrocytic vaccine approaches.

Emergence of genomic diversity and recurrent mutations in SARS-CoV-2.

SARS-CoV-2 is a SARS-like coronavirus of likely zoonotic origin first identified in December 2019 in Wuhan, the capital of China's Hubei province. The virus has since spread globally, resulting in the currently ongoing COVID-19 pandemic. The first whole genome sequence was published on January 5 2020, and thousands of genomes have been sequenced since this date. This resource allows unprecedented insights into the past demography of SARS-CoV-2 but also monitoring of how the virus is adapting to its novel human host, providing information to direct drug and vaccine design. We curated a dataset of 7666 public genome assemblies and analysed the emergence of genomic diversity over time. Our results are in line with previous estimates and point to all sequences sharing a common ancestor towards the end of 2019, supporting this as the period when SARS-CoV-2 jumped into its human host. Due to extensive transmission, the genetic diversity of the virus in several countries recapitulates a large fraction of its worldwide genetic diversity. We identify regions of the SARS-CoV-2 genome that have remained largely invariant to date, and others that have already accumulated diversity. By focusing on mutations which have emerged independently multiple times (homoplasies), we identify 198 filtered recurrent mutations in the SARS-CoV-2 genome. Nearly 80% of the recurrent mutations produced non-synonymous changes at the protein level, suggesting possible ongoing adaptation of SARS-CoV-2. Three sites in Orf1ab in the regions encoding Nsp6, Nsp11, Nsp13, and one in the Spike protein are characterised by a particularly large number of recurrent mutations (>15 events) which may signpost convergent evolution and are of particular interest in the context of adaptation of SARS-CoV-2 to the human host. We additionally provide an interactive user-friendly web-application to query the alignment of the 7666 SARS-CoV-2 genomes.

The Combined Effect of Oseltamivir and Favipiravir on Influenza A Virus Evolution.

Influenza virus inflicts a heavy death toll annually and resistance to existing antiviral drugs has generated interest in the development of agents with novel mechanisms of action. Favipiravir is an antiviral drug that acts by increasing the genome-wide mutation rate of influenza A virus (IAV). Potential synergistic benefits of combining oseltamivir and favipiravir have been demonstrated in animal models of influenza, but the population-level effects of combining the drugs are unknown. In order to elucidate the underlying evolutionary processes at play, we performed genome-wide sequencing of IAV experimental populations subjected to serial passaging in vitro under a combined protocol of oseltamivir and favipiravir. We describe the interplay between mutation, selection, and genetic drift that ultimately culminates in population extinction. In particular, selective sweeps around oseltamivir resistance mutations reduce genome-wide variation while deleterious mutations hitchhike to fixation given the increased mutational load generated by favipiravir. This latter effect reduces viral fitness and accelerates extinction compared with IAV populations treated with favipiravir alone, but risks spreading both established and newly emerging mutations, including possible drug resistance mutations, if transmission occurs before the viral populations are eradicated.

Two sides of the same coin: A population genetics perspective on lethal mutagenesis and mutational meltdown.

The extinction of RNA virus populations upon application of a mutagenic drug is frequently referred to as evidence for the existence of an error threshold, above which the population cannot sustain the mutational load. To explain the extinction process after reaching this threshold, models of lethal mutagenesis have been proposed, in which extinction is described as a deterministic (and thus population size-independent) process. As a separate body of literature, the population genetics community has developed models of mutational meltdown, which focus on the stochastic (and thus population-size dependent) processes governing extinction. However, recent extensions of both models have blurred these boundaries. Here, we first clarify definitions in terms of assumptions, expectations, and relevant parameter spaces, and then assess similarities and differences. As concepts from both fields converge, we argue for a unified theoretical framework that is focused on the evolutionary processes at play, rather than dispute over terminology.

The population genomics of rapid adaptation: disentangling signatures of selection and demography in white sands lizards.

Understanding the process of adaptation during rapid environmental change remains one of the central focal points of evolutionary biology. The recently formed White Sands system of southern New Mexico offers an outstanding example of rapid adaptation, with a variety of species having rapidly evolved blanched forms on the dunes that contrast with their close relatives in the surrounding dark soil habitat. In this study, we focus on two of the White Sands lizard species, Sceloporus cowlesi and Aspidoscelis inornata, for which previous research has linked mutations in the melanocortin-1 receptor gene (Mc1r) to blanched coloration. We sampled populations both on and off the dunes and used a custom sequence capture assay based on probed fosmid libraries to obtain >50 kb of sequence around Mc1r and hundreds of other random genomic locations. We then used model-based statistical inference methods to describe the demographic and adaptive history characterizing the colonization of White Sands. We identified a number of similarities between the two focal species, including strong evidence of selection in the blanched populations in the Mc1r region. We also found important differences between the species, suggesting different colonization times, different genetic architecture underlying the blanched phenotype and different ages of the beneficial alleles. Finally, the beneficial allele is dominant in S. cowlesi and recessive in A. inornata, allowing for a rare empirical test of theoretically expected patterns of selective sweeps under these differing models.

Inferring the age of a fixed beneficial allele.

Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype-based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian-based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype- and linkage disequilibrium-based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co-infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure.

Tracking the quality of care for sick children using lot quality assurance sampling: targeting improvements of health services in Jigawa, Nigeria.

BACKGROUND: In Nigeria, 30% of child deaths are due to malaria. The National Malaria Control Program of Nigeria (NMCP) during 2009 initiated a program to improve the quality of paediatric malaria services delivered in health facilities (HF). This study reports a rapid approach used to assess the existing quality of services in Jigawa state at decentralised levels of the health system. METHODS: NMCP selected Lot Quality Assurance Sampling (LQAS) to identify the variation in HF service quality among Senatorial Districts (SD). LQAS was selected because it was affordable and could be used by local health workers (HW) in a population-based survey. NMCP applied a 2-stage LQAS using a structured Rapid Health Facility Assessment (R-HFA) tool to identify high and low performing SD for specified indicators. FINDINGS: LQAS identified variations in HF performance (n = 21) and enabled resources to be targeted to address priorities. All SD exhibited deficient essential services, supplies and equipment. Only 9.7% of HF had Artemisinin-based Combination Therapies and other first-line treatments for childhood illnesses. No SD and few HF exhibited adequate HW performance for the assessment, treatment or counselling of sick children. Using the IMCI algorithm, 17.5% of HW assessed the child's vaccination status, 46.8% assessed nutritional status, and 65.1% assessed children for dehydration. Only 5.1% of HW treatments were appropriate for the assessment. Exit interviews revealed that 5.1% of caregivers knew their children's illness, and only 19.9% could accurately describe how to administer the prescribed drug. CONCLUSION: This R-HFA, using LQAS principles, is a rapid, simple tool for assessing malaria services and can be used at scale. It identified technical deficiencies that could be corrected by improved continuing medical education, targeted supervision, and recurrent R-HFA assessments of the quality of services.