adaPop: Bayesian inference of dependent population dynamics in coalescent models.

The coalescent is a powerful statistical framework that allows us to infer past population dynamics leveraging the ancestral relationships reconstructed from sampled molecular sequence data. In many biomedical applications, such as in the study of infectious diseases, cell development, and tumorgenesis, several distinct populations share evolutionary history and therefore become dependent. The inference of such dependence is a highly important, yet a challenging problem. With advances in sequencing technologies, we are well positioned to exploit the wealth of high-resolution biological data for tackling this problem. Here, we present adaPop, a probabilistic model to estimate past population dynamics of dependent populations and to quantify their degree of dependence. An essential feature of our approach is the ability to track the time-varying association between the populations while making minimal assumptions on their functional shapes via Markov random field priors. We provide nonparametric estimators, extensions of our base model that integrate multiple data sources, and fast scalable inference algorithms. We test our method using simulated data under various dependent population histories and demonstrate the utility of our model in shedding light on evolutionary histories of different variants of SARS-CoV-2.

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals.

Individuals infected with the SARS-CoV-2 virus present with a wide variety of symptoms ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe response to COVID-19. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the genetic predisposition to severe COVID-19 outcomes. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform a locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify four introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. Using reporter assays in the presence/absence of SARS-CoV-2, we find evidence that these variants respond to viral infection. These variants likely drive the locus' impact on severity by modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.

Severe COVID-19 May Impact Hepatic Fibrosis /Hepatic Stellate Cells Activation as Indicated by a Pathway and Population Genetic Study.

Coronavirus disease 19 (COVID-19) has affected over 112 million people and killed more than 2.5 million worldwide. When the pandemic was declared, Spain and Italy accounted for 29% of the total COVID-19 related deaths in Europe, while most infected patients did not present severe illness. We hypothesised that shared genomic characteristics, distinct from the rest of Europe, could be a contributor factor to a poor prognosis in these two populations. To identify pathways related to COVID-19 severity, we shortlisted 437 candidate genes associated with host viral intake and immune evasion from SARS-like viruses. From these, 21 were associated specifically with clinically aggressive COVID-19. To determine the potential mechanism of viral infections, we performed signalling pathway analysis with either the full list (n = 437) or the subset group (n = 21) of genes. Four pathways were significantly associated with the full gene list (Caveolar-mediated Endocytosis and the MSP-RON Signalling) or with the aggressive gene list (Hepatic Fibrosis/Hepatic Stellate Cell (HSC) Activation and the Communication between Innate and Adaptive Immune Cells). Single nucleotide polymorphisms (SNPs) from the ±1 Mb window of all genes related to these four pathways were retrieved from the dbSNP database. We then performed Principal Component analysis for these SNPs in individuals from the 1000 Genomes of European ancestry. Only the Hepatic Fibrosis/HSC Activation pathway showed population-specific segregation. The Spanish and Italian populations clustered together and away from the rest of the European ancestries, with the first segregating further from the rest. Additional in silico analysis identified potential genetic markers and clinically actionable therapeutic targets in this pathway, that may explain the severe disease.

Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally.

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, "2020 genomes" (N = 5959) sampled from December 2019 to September 2020 and "2021 genomes" (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40-199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies.

Geographical distribution of cystic fibrosis carriers as population genetic determinant of COVID-19 spread and fatality in 37 countries.

COVID-19 has shown a relevant heterogeneity in spread and fatality among countries together with a significant variability in its clinical presentation, indicating that host genetic factors may influence COVID-19 pathogenicity. Indeed, subjects carrying single pathogenic variants of the Cystic Fibrosis (CF) Transmembrane Conductance Regulator (CFTR) gene - i.e. CF carriers - are more susceptible to respiratory tract infections and are more likely to undergo severe COVID-19 with higher risk of 14-day mortality. Given that CF carrier prevalence varies among ethnicities and nations, an ecological study in 37 countries was conducted, in order to determine to what extent the diverse CF carrier geographical distribution may have affected COVID-19 spread and fatality during the first pandemic wave. The CF prevalence in countries, as indicator of the geographical distribution of CF carriers, significantly correlated in a direct manner with both COVID-19 prevalence and its Case Fatality Rate (CFR). In a regression study weighted for the number of tests performed, COVID-19 prevalence positively correlated with CF prevalence, while CFR correlated with population percentage older than 65-year, cancer and CF prevalence. Multivariate regression model also confirmed COVID-19 CFR to be associated with CF prevalence, after adjusting for elderly, cancer prevalence, and weighting for the number of tests performed. This study suggests a putative contribution of population genetics of CFTR in understanding the spatial distribution of COVID-19 spread and fatality.

Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants.

SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the genetic variation in these signaling networks remains uncharacterized. Here, we studied human missense single nucleotide variants (SNVs) altering phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid substitutions altering kinase-bound sequence motifs. We found 2,033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle and host responses, including RNA splicing, interferon response (TRIM28), and glucose homeostasis (TBC1D4) with potential associations with COVID-19 comorbidities. pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs of Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of signaling networks. Several pSNVs associate with severe COVID-19 and hospitalization (STARD13, ARFGEF2). Our analysis highlights potential genetic factors contributing to inter-individual variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.

Forecasting emergence of COVID-19 variants of concern.

We consider whether one can forecast the emergence of variants of concern in the SARS-CoV-2 outbreak and similar pandemics. We explore methods of population genetics and identify key relevant principles in both deterministic and stochastic models of spread of infectious disease. Finally, we demonstrate that fitness variation, defined as a trait for which an increase in its value is associated with an increase in net Darwinian fitness if the value of other traits are held constant, is a strong indicator of imminent transition in the viral population.

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.

Genetic diversity of SARS-CoV-2 in South America: demographic history and structuration signals.

In 2020, the emergence of SARS-CoV-2 caused a global public health crisis with significant mortality rates and a large socioeconomic burden. The rapid spread of this new virus has led to the appearance of new variants, making the characterization and monitoring of genetic diversity necessary to understand the population dynamics and evolution of the virus. Here, a population-genetics-based study was performed starting with South American genome sequences available in the GISAID database to investigate the genetic diversity of SARS-CoV-2 on this continent and the evolutionary mechanisms that modulate it.

Comparative Y-chromosome analysis among Cypriots in the context of historical events and migrations.

Y-chromosome analysis provides valuable information regarding the migration patterns of male ancestors, ranging from the Paleolithic age to the modern humans. STR and SNP genotyping analysis provides data regarding the genetic and geographical ancestry of the populations studied. This study focused on the analysis of the Y-chromosome in Maronite Cypriots and Armenian Cypriots, who came to the island as a result of different historical events. The aim was to provide information on the paternal genetic ancestry of Maronites and Armenians of Cyprus and investigate any affinity with the Greek Cypriots and Turkish Cypriots of the island. Since there is limited information in the current literature, we proceeded and used 23 Y-chromosome STRs and 28 Y-chromosome SNPs to genotype 57 Maronite Cypriots and 56 Armenian Cypriots, which were then compared to data from 344 Greek Cypriots and 380 Turkish Cypriots. All samples were assigned to eight major Y-haplogroups but the most frequent haplogroup among all Cypriots is haplogroup J in the major subclade J2a-L559. The calculated pairwise genetic distances between the populations show that Armenian Cypriots are genetically closer to Greek and Turkish Cypriots compared to Maronite Cypriots. Median Joining Network analysis in 17 Y-STR haplotypes of all Cypriots assigned to J2a-L559, revealed that Cypriots share a common paternal ancestor, prior to the migration of the Armenians and Maronites to Cyprus, estimated in the Late Bronze Age and Early Iron Age.

New insights into human immunity from ancient genomics.

Population genetic studies have clearly indicated that immunity and host defense are among the functions most frequently subject to natural selection, and increased our understanding of the biological relevance of the corresponding genes and their contribution to variable immune traits and diseases. Herein, we will focus on some recently studied forms of human adaptation to infectious agents, including hybridization with now-extinct hominins, such as Neanderthals and Denisovans, and admixture between modern human populations. These studies, which are partly enabled by the technological advances in the sequencing of DNA from ancient remains, provide new insight into the sources of immune response variation in contemporary humans, such as the recently reported link between Neanderthal heritage and susceptibility to severe COVID-19 disease. Furthermore, ancient DNA analyses, in both humans and pathogens, allow to measure the action of natural selection on immune genes across time and to reconstruct the impact of past epidemics on the evolution of human immunity.

Describing variability in pig genes involved in coronavirus infections for a One Health perspective in conservation of animal genetic resources.

Coronaviruses silently circulate in human and animal populations, causing mild to severe diseases. Therefore, livestock are important components of a "One Health" perspective aimed to control these viral infections. However, at present there is no example that considers pig genetic resources in this context. In this study, we investigated the variability of four genes (ACE2, ANPEP and DPP4 encoding for host receptors of the viral spike proteins and TMPRSS2 encoding for a host proteinase) in 23 European (19 autochthonous and three commercial breeds and one wild boar population) and two Asian Sus scrofa populations. A total of 2229 variants were identified in the four candidate genes: 26% of them were not previously described; 29 variants affected the protein sequence and might potentially interact with the infection mechanisms. The results coming from this work are a first step towards a "One Health" perspective that should consider conservation programs of pig genetic resources with twofold objectives: (i) genetic resources could be reservoirs of host gene variability useful to design selection programs to increase resistance to coronaviruses; (ii) the described variability in genes involved in coronavirus infections across many different pig populations might be part of a risk assessment including pig genetic resources.

Population-Specific ACE2 Single-Nucleotide Polymorphisms Have Limited Impact on SARS-CoV-2 Infectivity In Vitro.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), employs host-cell angiotensin-converting enzyme 2 (ACE2) for cell entry. Genetic analyses of ACE2 have identified several single-nucleotide polymorphisms (SNPs) specific to different human populations. Molecular dynamics simulations have indicated that several of these SNPs could affect interactions between SARS-CoV-2 and ACE2, thereby providing a partial explanation for the regional differences observed in SARS-CoV-2 infectivity and severity. However, the significance of population-specific ACE2 SNPs in SARS-CoV-2 infectivity is unknown, as no in vitro validation studies have been performed. Here, we analyzed the impact of eight SNPs found in specific populations on receptor binding and cell entry in vitro. Except for a SNP causing a nonsense mutation that reduced ACE2 expression, none of the selected SNPs markedly altered the interaction between ACE2 and the SARS-CoV-2 spike protein (SARS-2-S), which is responsible for receptor recognition and cell entry, or the efficiency of viral cell entry mediated by SARS-2-S. Our findings indicate that ACE2 polymorphisms have limited impact on the ACE2-dependent cell entry of SARS-CoV-2 and underscore the importance of future studies on the involvement of population-specific SNPs of other host genes in susceptibility toward SARS-CoV-2 infection.

ACE2 and TMPRSS2 polymorphisms in various diseases with special reference to its impact on COVID-19 disease.

BACKGROUND: A carboxypeptidase protein called ACE2 is found in many organs. ACE2 protein can play a pivotal role to regulate the pathological changes of several diseases including COVID-19. TMPRSS2 gene is expressed in many human tissues and plays a critical role in spreading the infection of the viruses including coronavirus and progression of prostate cancer, and hence could be used as a potential drug target. There are limited reports on occurrence of genetic polymorphism of ACE2 and TMPRSS2 in general population, expressions in pathological conditions, and its impact on COVID-19 disease. Hence we comprehended the occurrence of ACE2, TMPRSS2 polymorphism in general population, expression in various diseases and its impact on COVID-19 disease. METHOD: We utilized multiple databases, PubMed (Medline), EMBASE and Google Scholar for literature search. DESCRIPTION: ACE2 polymorphisms have significant linkages with various diseases, including severity of SARS-CoV-2 infection. Genetic variations of these genes contribute to individual's genetic susceptibility to viral infection and its subsequent clearance. The diversity and variations in the population distribution of these genes, might greatly influence and in turn reflect into the observed population and gender differences of the severity and clinical outcomes of SARS-CoV-2 infection. CONCLUSION: There are diversities in distribution of ACE2 and TMPRSS2 polymorphisms among different populations. Analyzing the genetic variants and expression of ACE2 and TMPRSS2 genes, in a population may provide the genetic marker for susceptibility or resistance against the coronavirus infection, which might be useful for identifying the susceptible population groups for targeted interventions and for making relevant public health policy decisions.

Understanding evolution of SARS-CoV-2: A perspective from analysis of genetic diversity of RdRp gene.

Coronavirus disease 2019 emerged as the first example of "Disease X", a hypothetical disease of humans caused by an unknown infectious agent that was named as novel coronavirus and subsequently designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The origin of the outbreak at the animal market in Wuhan, China implies it as a case of zoonotic spillover. The study was designed to understand evolution of Betacoronaviruses and in particular diversification of SARS-CoV-2 using RNA dependent RNA polymerase (RdRp) gene, a stable genetic marker. Phylogenetic and population stratification analyses were carried out using maximum likelihood and Bayesian methods, respectively. Molecular phylogeny using RdRp showed that SARS-CoV-2 isolates cluster together. Bat-CoV isolate RaTG13 and Pangolin-CoVs are observed to branch off prior to SARS-CoV-2 cluster. While SARS-CoV form a single cluster, Bat-CoVs form multiple clusters. Population-based analyses revealed that both SARS-CoV-2 and SARS-CoV form separate clusters with no admixture. Bat-CoVs were found to have single and mixed ancestry and clustered as four sub-populations. Population-based analyses of Betacoronaviruses using RdRp revealed that SARS-CoV-2 is a homogeneous population. SARS-CoV-2 appears to have evolved from Bat-CoV isolate RaTG13, which diversified from a common ancestor from which Pangolin-CoVs have also evolved. The admixed Bat-CoV sub-populations indicate that bats serve as reservoirs harboring virus ensembles that are responsible for zoonotic spillovers such as SARS-CoV and SARS-CoV-2. The extent of admixed isolates of Bat-CoVs observed in population diversification studies underline the need for periodic surveillance of bats and other animal reservoirs for potential spillovers as a measure towards preparedness for emergence of zoonosis.

Correlation of the two most frequent HLA haplotypes in the Italian population to the differential regional incidence of Covid-19.

BACKGROUND: Understanding how HLA polymorphisms may affect both susceptibility, course and severity of Covid-19 infection could help both at the clinical level to identify individuals at higher risk from the disease and at the epidemiological one to explain the differences in the epidemic trend among countries or even within a specific country. Covid-19 disease in Italy showed a peculiar geographical distribution from the northern most affected regions to the southern ones only slightly touched. METHODS: In this study we analysed the regional frequencies for the most common Italian haplotypes from the Italian Bone Marrow Donor Registry (HLA-A, -B, -C and -DRB1 at four-digit level). Then we performed Pearson correlation analyses among regional haplotypes estimated frequency in the population and Covid-19 incidence and mortality. RESULTS: In this study we found that the two most frequent HLA haplotypes in the Italian population, HLA-A*:01:01g-B*08:01 g-C*07:01g-DRB1*03:01g and HLA-A*02.01g-B*18.01g-C*07.01g-DRB1*11.04g, had a regional distribution overlapping that of Covid-19 and showed respectively a positive (suggestive of susceptibility) and negative (suggestive of protection) significant correlation with both Covid-19 incidence and mortality. CONCLUSIONS: Based on these results, in order to define such HLA haplotypes as a factor effectively associated to the disease susceptibility, the creation of national networks that can collect patients' samples from all regions for HLA typing should be highly encouraged.

New insights into genetic susceptibility of COVID-19: an ACE2 and TMPRSS2 polymorphism analysis.

BACKGROUND: Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has now been confirmed worldwide. Yet, COVID-19 is strangely and tragically selective. Morbidity and mortality due to COVID19 rise dramatically with age and co-existing health conditions, including cancer and cardiovascular diseases. Human genetic factors may contribute to the extremely high transmissibility of SARS-CoV-2 and to the relentlessly progressive disease observed in a small but significant proportion of infected individuals, but these factors are largely unknown. MAIN BODY: In this study, we investigated genetic susceptibility to COVID-19 by examining DNA polymorphisms in ACE2 and TMPRSS2 (two key host factors of SARS-CoV-2) from ~ 81,000 human genomes. We found unique genetic susceptibility across different populations in ACE2 and TMPRSS2. Specifically, ACE2 polymorphisms were found to be associated with cardiovascular and pulmonary conditions by altering the angiotensinogen-ACE2 interactions, such as p.Arg514Gly in the African/African-American population. Unique but prevalent polymorphisms (including p.Val160Met (rs12329760), an expression quantitative trait locus (eQTL)) in TMPRSS2, offer potential explanations for differential genetic susceptibility to COVID-19 as well as for risk factors, including those with cancer and the high-risk group of male patients. We further discussed that polymorphisms in ACE2 or TMPRSS2 could guide effective treatments (i.e., hydroxychloroquine and camostat) for COVID-19. CONCLUSION: This study suggested that ACE2 or TMPRSS2 DNA polymorphisms were likely associated with genetic susceptibility of COVID-19, which calls for a human genetics initiative for fighting the COVID-19 pandemic.