Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models

Associations between epidemiological and laboratory parameters and disease severity in hospitalized patients with COVID-19 during first and second epidemic waves in middle south Mato Grosso

BACKGROUND

COVID-19 is a multisystemic disease characterized by respiratory distress. Disease severity is associated with several factors. Here we characterize virological findings and evaluate the association of laboratorial, epidemiological, virological findings and clinical outcomes of 251 patients during the first and second epidemic waves of COVID-19.

METHODS

This transversal study used biological samples and data from patients hospitalized with COVID-19 between May 2020 and August 2021 in the metropolitan region of Cuiabá, Mato Grosso Brazil. Biological samples were subjected to RT-qPCR and MinION sequencing. Univariate and multivariate logistic regression and Odds ratio were used to correlate clinical, laboratorial, epidemiological data.

FINDINGS

Patients were represented by males (61.7%) with mean age of 52.4 years, mild to moderate disease (49,0%), overweight/obese (69.3%), with comorbidities (66.1%) and evolving to death (55.38%). Severe cases showing symptoms for prolonged time, ≥ 25% of ground-glass opacities in the lungs and fatality rate increased significantly in second wave. Fatality was statistically associated to > 61 years of age,>25% ground-glass opacities in the lungs, immune, cardiac, or metabolic comorbidities. Higher viral load (p < 0.01/p = 0.02 in each wave), decreased erythrocyte (p < 0.01), hemoglobin (p < 0.05/p < 0.01), hematocrit (p < 0.01), RDW (p < 0.01), lymphocyte (p < 0.01), increased leucocyte (p < 0.01), neutrophil (p < 0.01) and CRP levels (p < 0.01) showed significant association with fatality in both waves, as did Neutrophil/Platelet (NPR; p < 0.01), Neutrophil/Lymphocyte (NLR; p < 0.01) and Monocyte/Lymphocyte ratio (MLR; p < 0.01). SARS-CoV-2 genomes from lineage B.1.1.33(n = 8) and Gamma/P.1(n = 15) shared 6/7 and 20/23 lineage-defining mutations, respectively.

MAIN CONCLUSIONS

Severity and mortality of COVID-19 associated with a panel of epidemiological and laboratorial findings, being second wave, caused by Gamma variant, more severe in this in-hospital population.

Evolution of Sequence and Structure of SARS-CoV-2 Spike Protein: A Dynamic Perspective

Novel coronavirus (SARS-CoV-2) enters its host cell through a surface spike protein. The viral spike protein has undergone several modifications/mutations at the genomic level, through which it modulated its structure-function and passed through several variants of concern. Recent advances in high-resolution structure determination and multiscale imaging techniques, cost-effective next-generation sequencing, and development of new computational methods (including information theory, statistical methods, machine learning, and many other artificial intelligence-based techniques) have hugely contributed to the characterization of sequence, structure, function of spike proteins, and its different variants to understand viral pathogenesis, evolutions, and transmission. Laying on the foundation of the sequence-structure-function paradigm, this review summarizes not only the important findings on structure/function but also the structural dynamics of different spike components, highlighting the effects of mutations on them. As dynamic fluctuations of three-dimensional spike structure often provide important clues for functional modulation, quantifying time-dependent fluctuations of mutational events over spike structure and its genetic/amino acidic sequence helps identify alarming functional transitions having implications for enhanced fusogenicity and pathogenicity of the virus. Although these dynamic events are more difficult to capture than quantifying a static, average property, this review encompasses those challenging aspects of characterizing the evolutionary dynamics of spike sequence and structure and their implications for functions.

Early warning of emerging infectious diseases based on multimodal data

The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information. Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control. This review summarized the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants. As people have suffered from COVID-19 and repeated flu outbreaks, we focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses. This review comprehensively viewed the latest virus research and provided a reference for future virus prevention and control research.

L-shaped distribution of the relative substitution rate (c/μ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Evolution of SARS-CoV-2 during the first year of the COVID-19 pandemic in Northwestern Argentina

Studies about the evolution of SARS-CoV-2 lineages in different backgrounds such as naive populations are still scarce, especially from South America. This work aimed to study the introduction and diversification pattern of SARS-CoV-2 during the first year of the COVID-19 pandemic in the Northwestern Argentina (NWA) region and to analyze the evolutionary dynamics of the main lineages found. In this study, we analyzed a total of 260 SARS-CoV-2 whole-genome sequences from Argentina, belonging to the Provinces of Jujuy, Salta, and Tucumán, from March 31st, 2020, to May 22nd, 2021, which covered the full first wave and the early second wave of the COVID-19 pandemic in Argentina. In the first wave, eight lineages were identified: B.1.499 (76.9%), followed by N.5 (10.2%), B.1.1.274 (3.7%), B.1.1.348 (3.7%), B.1 (2.8%), B.1.600 (0.9%), B.1.1.33 (0.9%) and N.3 (0.9%). During the early second wave, the first-wave lineages were displaced by the introduction of variants of concern (VOC) (Alpha, Gamma), or variants of interest (VOI) (Lambda, Zeta, Epsilon) and other lineages with more limited distribution. Phylodynamic analyses of the B.1.499 and N.5, the two most prevalent lineages in the NWA, revealed that the rate of evolution of lineage N.5 (7.9 × 10-4 substitutions per site per year, s/s/y) was a ∼40% faster than that of lineage B.1.499 (5.6 × 10-4 s/s/y), although both are in the same order of magnitude than other non-VOC lineages. No mutations associated with a biological characteristic of importance were observed as signatures markers of the phylogenetic groups established in Northwestern Argentina, however, single sequences in non-VOC lineages did present mutations of biological importance or associated with VOCs as sporadic events, showing that many of these mutations could emerge from circulation in the general population. This study contributed to the knowledge about the evolution of SARS-CoV-2 in a pre-vaccination and without post-exposure immunization period.

A Glimpse on the Evolution of RNA Viruses: Implications and Lessons from SARS-CoV-2

RNA viruses are characterised by extremely high genetic variability due to fast replication, large population size, low fidelity, and (usually) a lack of proofreading mechanisms of RNA polymerases leading to high mutation rates. Furthermore, viral recombination and reassortment may act as a significant evolutionary force among viruses contributing to greater genetic diversity than obtainable by mutation alone. The above-mentioned properties allow for the rapid evolution of RNA viruses, which may result in difficulties in viral eradication, changes in virulence and pathogenicity, and lead to events such as cross-species transmissions, which are matters of great interest in the light of current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemics. In this review, we aim to explore the molecular mechanisms of the variability of viral RNA genomes, emphasising the evolutionary trajectory of SARS-CoV-2 and its variants. Furthermore, the causes and consequences of coronavirus variation are explored, along with theories on the origin of human coronaviruses and features of emergent RNA viruses in general. Finally, we summarise the current knowledge on the circulating variants of concern and highlight the many unknowns regarding SARS-CoV-2 pathogenesis.

Understanding the mutational frequency in SARS-CoV-2 proteome using structural features

The prolonged transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in the human population has led to demographic divergence and the emergence of several location-specific clusters of viral strains. Although the effect of mutation(s) on severity and survival of the virus is still unclear, it is evident that certain sites in the viral proteome are more/less prone to mutations. In fact, millions of SARS-CoV-2 sequences collected all over the world have provided us a unique opportunity to understand viral protein mutations and develop novel computational approaches to predict mutational patterns. In this study, we have classified the mutation sites into low and high mutability classes based on viral isolates count containing mutations. The physicochemical features and structural analysis of the SARS-CoV-2 proteins showed that features including residue type, surface accessibility, residue bulkiness, stability and sequence conservation at the mutation site were able to classify the low and high mutability sites. We further developed machine learning models using above-mentioned features, to predict low and high mutability sites at different selection thresholds (ranging 5-30% of topmost and bottommost mutated sites) and observed the improvement in performance as the selection threshold is reduced (prediction accuracy ranging from 65 to 77%). The analysis will be useful for early detection of variants of concern for the SARS-CoV-2, which can also be applied to other existing and emerging viruses for another pandemic prevention.

A Paradigm Shift in the Combination Changes of SARS-CoV-2 Variants and Increased Spread of Delta Variant (B.1.617.2) across the World

Since September 2020, the SARS-CoV-2 variants have gained their dominance worldwide, especially in Kenya, Italy, France, the UK, Turkey, Indonesia, India, Finland, Ireland, Singapore, Denmark, Germany, and Portugal. In this study, we developed a model on the frequency of delta variants across 28 countries (R²= 0.1497), displaying the inheritance of mutations during the generation of the delta variants with 123,526 haplotypes. The country-wise haplotype network showed the distribution of haplotypes in USA (10,174), Denmark (5,637), India (4,089), Germany (2,350), Netherlands (1,899), Sweden (1,791), Italy (1,720), France (1,293), Ireland (1,257), Belgium (1,207), Singapore (1,193), Portugal (1,184) and Spain (1,133). Our analysis shows the highest haplotype in Europe with 84% and the lowest in Australia with 0.00001%. A model of scatter plot was generated with a regression line which provided the estimated rate of mutation, including 24.048 substitutions yearly. Our study concluded that the high global prevalence of the delta variants is due to a high frequency of infectivity, supporting the paradigm shift of the viral variants.

The status and analysis of common mutations found in the SARS-CoV-2 whole genome sequences from Bangladesh

Rapid emergence of covid-19 variants by continuous mutation made the world experience continuous waves of infections and as a result, a huge number of death-toll recorded so far. It is, therefore, very important to investigate the diversity and nature of the mutations in the SARS-CoV-2 genomes. In this study, the common mutations occurred in the whole genome sequences of SARS-CoV-2 variants of Bangladesh in a certain timeline were analyzed to better understand its status. Hence, a total of 78 complete genome sequences available in the NCBI database were obtained, aligned and further analyzed. Scattered Single Nucleotide Polymorphisms (SNPs) were identified throughout the genome of variants and common SNPs such as: 241:C>T in the 5′UTR of Open Reading Frame 1A (ORF1A), 3037: C>T in Non-structural Protein 3 (NSP3), 14,408: C>T in ORF6 and 23,402: A>G, 23,403: A>G in Spike Protein (S) were observed, but all of them were synonymous mutations. About 97% of the studied genomes showed a block of tri-nucleotide alteration (GGG>AAC), the most common non-synonymous mutation in the 28,881–28,883 location of the genome. This block results in two amino acid changes (203–204: RG>KR) in the SR rich motif of the nucleocapsid (N) protein of SARS-CoV-2, introducing a lysine in between serine and arginine. The N protein structure of the mutant was predicted through protein modeling. However, no observable difference was found between the mutant and the reference (Wuhan) protein. Further, the protein stability changes upon mutations were analyzed using the I-Mutant2.0 tool. The alteration of the arginine to lysine at the amino acid position 203, showed reduction of entropy, suggesting a possible impact on the overall stability of the N protein. The estimation of the non-synonymous to synonymous substitution ratio (dN/dS) were analyzed for the common mutations and the results showed that the overall mean distance among the N-protein variants were statistically significant, supporting the non-synonymous nature of the mutations. The phylogenetic analysis of the selected 78 genomes, compared with the most common genomic variants of this virus across the globe showed a distinct cluster for the analyzed Bangladeshi sequences. Further studies are warranted for conferring any plausible association of these mutations with the clinical manifestation.

Genetic Surveillance of Five SARS-CoV-2 Clinical Samples in Henan Province Using Nanopore Sequencing

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread and poses a major threat to public health worldwide. The whole genome sequencing plays a crucial role in virus surveillance and evolutionary analysis. In this study, five genome sequences of SARS-CoV-2 were obtained from nasopharyngeal swab samples from Zhengzhou, China. Following RNA extraction and cDNA synthesis, multiplex PCR was performed with two primer pools to produce the overlapped amplicons of ~1,200 bp. The viral genomes were obtained with 96% coverage using nanopore sequencing. Forty-five missense nucleotide mutations were identified; out of these, 5 mutations located at Nsp2, Nsp3, Nsp14, and ORF10 genes occurred with a <0.1% frequency in the global dataset. On the basis of mutation profiles, five genomes were clustered into two sublineages (B.1.617.2 and AY.31) or subclades (21A and 21I). The phylogenetic analysis of viral genomes from several regions of China and Myanmar revealed that five patients had different viral transmission chains. Taken together, we established a nanopore sequencing platform for genetic surveillance of SARS-CoV-2 and identified the variants circulating in Zhengzhou during August 2021. Our study provided crucial support for government policymaking and prevention and control of COVID-19.

Phylogenetic and genome-wide mutational analysis of SARS-CoV-2 strains circulating in Nigeria: no implications for attenuated COVID-19 outcomes

OBJECTIVES

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The COVID-19 incidence and mortality rates are low in Nigeria compared to global trends. This research mapped the evolution of SARS-CoV-2 circulating in Nigeria and globally to determine whether the Nigerian isolates are genetically distinct from strains circulating in regions of the world with a high disease burden.

METHODS

Bayesian phylogenetics using BEAST 2.0, genetic similarity analyses, and genomewide mutational analyses were used to characterize the strains of SARS-CoV-2 isolated in Nigeria.

RESULTS

SARS-CoV-2 strains isolated in Nigeria showed multiple lineages and possible introductions from Europe and Asia. Phylogenetic clustering and sequence similarity analyses demonstrated that Nigerian isolates were not genetically distinct from strains isolated in other parts of the globe. Mutational analysis demonstrated that the D614G mutation in the spike protein, the P323L mutation in open reading frame 1b (and more specifically in NSP12), and the R203K/ G204R mutation pair in the nucleocapsid protein were most prevalent in the Nigerian isolates.

CONCLUSION

The SARS-CoV-2 strains in Nigeria were neither phylogenetically nor genetically distinct from virus strains circulating in other countries of the world. Thus, differences in SARS-CoV-2 genomes are not a plausible explanation for the attenuated COVID-19 outcomes in Nigeria.

Clinical and genomic data of sars-cov-2 detected in maternal-fetal interface during the first wave of infection in brazil

Brazil has the highest SARS-CoV-2 case-fatality rate in pregnant women in the Americas. In this study, clinical and virological findings of five mildly symptomatic pregnant women and their infected fetuses/newborns treated at a referral hospital for COVID19-pregnant women in Midwestern Brazil are reported. Mother and fetal samples were tested by RT-qPCR, ECLIA and Illumina MiSeq sequencing. From the five cases, one resulted in spontaneous abortion, one was stillborn, two were preterm births and one full-term birth. Maternal and fetal placenta, newborn and stillborn secretions were SARS-CoV-2+; one neonate developed ground-glass opacities in his lungs. One neonate's umbilical cord was IgG+ and all were IgM negative upon hospital discharge. Genomes recovered from two placentas belong to the B.1.1.28 and B.1.1.33 lineages and present nonsynonymous mutations associated with virus fitness and infectivity; other not frequently reported mutations (B.1.1.33: NSP3 V2090G, M A2S and ORF3ab S253P and Y264N; B.1.1.28: NSP3 E995D, NSP12 R240K, NSP14H1897Y and in ORF7b V21F) were found in proteins involved in viral replication, viral induction of apoptosis, viral interference on interferon and on NF-Κβ pathways. Phylogeny indicates the south of Brazil as the possible origin of these lineages circulating in Mato Grosso State. These findings contribute to describe SARS-CoV-2 infection and outcomes in pregnant women and their fetuses, at any stage of gestation and even in mild symptomatic cases.

Epidemiology and Genetic Analysis of SARS-CoV-2 in Myanmar during the Community Outbreaks in 2020

We aimed to analyze the situation of the first two epidemic waves in Myanmar using the publicly available daily situation of COVID-19 and whole-genome sequencing data of SARS-CoV-2. From March 23 to December 31, 2020, there were 33,917 confirmed cases and 741 deaths in Myanmar (case fatality rate of 2.18%). The first wave in Myanmar from March to July was linked to overseas travel, and then a second wave started from Rakhine State, a western border state, leading to the second wave spreading countrywide in Myanmar from August to December 2020. The estimated effective reproductive number (R_t) nationwide reached 6–8 at the beginning of each wave and gradually decreased as the epidemic spread to the community. The whole-genome analysis of 10 Myanmar SARS-CoV-2 strains together with 31 previously registered strains showed that the first wave was caused by GISAID clade O or PANGOLIN lineage B.6 and the second wave was changed to clade GH or lineage B.1.36.16 with a close genetic relationship with other South Asian strains. Constant monitoring of epidemiological situations combined with SARS-CoV-2 genome analysis is important for adjusting public health measures to mitigate the community transmissions of COVID-19.

Antiviral Strategies Against SARS-CoV-2: A Systems Biology Approach

The unprecedented scientific achievements in combating the COVID-19 pandemic reflect a global response informed by unprecedented access to data. We now have the ability to rapidly generate a diversity of information on an emerging pathogen and, by using high-performance computing and a systems biology approach, we can mine this wealth of information to understand the complexities of viral pathogenesis and contagion like never before. These efforts will aid in the development of vaccines, antiviral medications, and inform policymakers and clinicians. Here we detail computational protocols developed as SARS-CoV-2 began to spread across the globe. They include pathogen detection, comparative structural proteomics, evolutionary adaptation analysis via network and artificial intelligence methodologies, and multiomic integration. These protocols constitute a core framework on which to build a systems-level infrastructure that can be quickly brought to bear on future pathogens before they evolve into pandemic proportions.

Evolutionary analysis and lineage designation of SARS-CoV-2 genomes

The pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), has caused immense global disruption. With the rapid accumulation of SARS-CoV-2 genome sequences, however, thousands of genomic variants of SARS-CoV-2 are now publicly available. To improve the tracing of the viral genomes' evolution during the development of the pandemic, we analyzed single nucleotide variants (SNVs) in 121,618 high-quality SARS-CoV-2 genomes. We divided these viral genomes into two major lineages (L and S) based on variants at sites 8782 and 28144, and further divided the L lineage into two major sublineages (L1 and L2) using SNVs at sites 3037, 14408, and 23403. Subsequently, we categorized them into 130 sublineages (37 in S, 35 in L1, and 58 in L2) based on marker SNVs at 201 additional genomic sites. This lineage/sublineage designation system has a hierarchical structure and reflects the relatedness among the subclades of the major lineages. We also provide a companion website (www.covid19evolution.net) that allows users to visualize sublineage information and upload their own SARS-CoV-2 genomes for sublineage classification. Finally, we discussed the possible roles of compensatory mutations and natural selection during SARS-CoV-2's evolution. These efforts will improve our understanding of the temporal and spatial dynamics of SARS-CoV-2's genome evolution.

The Evolutionary Landscape of SARS-CoV-2 Variant B.1.1.519 and Its Clinical Impact in Mexico City

The SARS-CoV-2 pandemic is one of the most concerning health problems around the globe. We reported the emergence of SARS-CoV-2 variant B.1.1.519 in Mexico City. We reported the effective reproduction number (Rt) of B.1.1.519 and presented evidence of its geographical origin based on phylogenetic analysis. We also studied its evolution via haplotype analysis and identified the most recurrent haplotypes. Finally, we studied the clinical impact of B.1.1.519. The B.1.1.519 variant was predominant between November 2020 and May 2021, reaching 90% of all cases sequenced in February 2021. It is characterized by three amino acid changes in the spike protein: T478K, P681H, and T732A. Its Rt varies between 0.5 and 2.9. Its geographical origin remain to be investigated. Patients infected with variant B.1.1.519 showed a highly significant adjusted odds ratio (aOR) increase of 1.85 over non-B.1.1.519 patients for developing a severe/critical outcome (p = 0.000296, 1.33-2.6 95% CI) and a 2.35-fold increase for hospitalization (p = 0.005, 1.32-4.34 95% CI). The continuous monitoring of this and other variants will be required to control the ongoing pandemic as it evolves.

A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

Background

Québec was the Canadian province most impacted by COVID-19, with 401,462 cases as of September 24th, 2021, and 11,347 deaths due mostly to a very severe first pandemic wave. In April 2020, we assembled the Coronavirus Sequencing in Québec (CoVSeQ) consortium to sequence SARS-CoV-2 genomes in Québec to track viral introduction events and transmission within the province.

Methods

Using genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec. We report 2921 high-quality SARS-CoV-2 genomes in the context of > 12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatiotemporal spread of the virus.

Results

Conservatively, we estimated approximately 600 independent introduction events, the majority of which happened from spring break until 2 weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (> 50 sequenced cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and “snowbird” destinations, most of the introductions were inferred to have originated from Europe via the Americas. Once introduced into Québec, viral lineage sizes were overdispersed, with a few lineages giving rise to most infections. Consistent with founder effects, the earliest lineages to arrive tended to spread most successfully. Fewer than 100 viral introductions arrived during spring break, of which 7–12 led to the largest transmission lineages of the first wave (accounting for 52–75% of all sequenced infections). These successful transmission lineages dispersed widely across the province. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travellers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order.

Conclusions

Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00986-9.

Interpretable machine learning for genomics

High-throughput technologies such as next-generation sequencing allow biologists to observe cell function with unprecedented resolution, but the resulting datasets are too large and complicated for humans to understand without the aid of advanced statistical methods. Machine learning (ML) algorithms, which are designed to automatically find patterns in data, are well suited to this task. Yet these models are often so complex as to be opaque, leaving researchers with few clues about underlying mechanisms. Interpretable machine learning (iML) is a burgeoning subdiscipline of computational statistics devoted to making the predictions of ML models more intelligible to end users. This article is a gentle and critical introduction to iML, with an emphasis on genomic applications. I define relevant concepts, motivate leading methodologies, and provide a simple typology of existing approaches. I survey recent examples of iML in genomics, demonstrating how such techniques are increasingly integrated into research workflows. I argue that iML solutions are required to realize the promise of precision medicine. However, several open challenges remain. I examine the limitations of current state-of-the-art tools and propose a number of directions for future research. While the horizon for iML in genomics is wide and bright, continued progress requires close collaboration across disciplines.

Effects of government policies on the spread of COVID-19 worldwide

The outbreak of novel COVID-19 disease elicited a wide range of anti-contagion and economic policies like school closure, income support, contact tracing, and so forth, in the mitigation and suppression of the spread of the SARS-CoV-2 virus. However, a systematic evaluation of these policies has not been made. Here, 17 implemented policies from the Oxford COVID-19 Government Response Tracker dataset employed in 90 countries from December 31, 2019, to August 31, 2020, were analyzed. A Poisson regression model was applied to analyze the relationship between policies and daily confirmed cases using a generalized estimating equations approach. A lag is a fixed time displacement in time series data. With that, lagging (0, 3, 7, 10, and 14 days) was also considered during the analysis since the effects of policies implemented on a given day may affect the number of confirmed cases several days after implementation. The countries were divided into three groups depending on the number of waves of the pandemic observed in each country. Through subgroup analysis, we showed that with and without lagging, contact tracing and containment policies were significant for countries with two waves, while closing, economic, and health policies were significant for countries with three waves. Wave-specific analysis for each wave showed that significant health, economic, and containment policies varied across waves of the pandemic. Emergency investment in healthcare was consistently significant among the three groups of countries, while the Stringency index was significant among all waves of the pandemic. These findings may help in making informed decisions regarding whether, which, or when these policies should be intensified or lifted.

OntoRepliCov: an Ontology-Based Approach for Modeling the SARS-CoV-2 Replication Process

Understanding the replication machinery of viruses contributes to suggest and try effective antiviral strategies. Exhaustive knowledge about the proteins structure, their function, or their interaction is one of the preconditions for successfully modeling it. In this context, modeling methods based on a formal representation with a high semantic expressiveness would be relevant to extract proteins and their nucleotide or amino acid sequences as an element from the replication process. Consequently, our approach relies on the use of semantic technologies to design the SARS-CoV-2 replication machinery. This provides the ability to infer new knowledge related to each step of the virus replication. More specifically, we developed an ontology-based approach enriched with reasoning process of a complete replication machinery process for SARS-CoV-2. We present in this paper a partial overview of our ontology OntoRepliCov to describe one step of this process, namely, the continuous translation or protein synthesis, through classes, properties, axioms, and SWRL (Semantic Web Rule Language) rules.

SARS-CoV-2 spike protein: pathogenesis, vaccines, and potential therapies

PURPOSE

COVID-19 pandemic has emerged as a result of infection by the deadly pathogenic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), causing enormous threats to humans. Coronaviruses are distinguished by a clove-like spike (S) protein, which plays a key role in viral pathogenesis, evolutions, and transmission. The objectives of this study are to investigate the distinctive structural features of SARS-CoV-2 S protein, its essential role in pathogenesis, and its use in the development of potential therapies and vaccines.

METHODOLOGY

A literature review was conducted to summarize, analyze, and interpret the available scientific data related to SARS-CoV-2 S protein in terms of characteristics, vaccines development and potential therapies.

RESULTS

The data indicate that S protein subunits and their variable conformational states significantly affect the virus pathogenesis, infectivity, and evolutionary mutation. A considerable number of potential natural and synthetic therapies were proposed based on S protein. Additionally, neutralizing antibodies were recently approved for emergency use. Furthermore, several vaccines utilizing the S protein were developed.

CONCLUSION

A better understanding of S protein features, structure and mutations facilitate the recognition of the importance of SARS-CoV-2 S protein in viral infection, as well as the development of therapies and vaccines. The efficacy and safety of these therapeutic compounds and vaccines are still controversial. However, they may potentially reduce or prevent SARS-CoV-2 infection, leading to a significant reduction of the global health burden of this pandemic.

The emergence and ongoing convergent evolution of the SARS-CoV-2 N501Y lineages

The independent emergence late in 2020 of the B.1.1.7, B.1.351, and P.1 lineages of SARS-CoV-2 prompted renewed concerns about the evolutionary capacity of this virus to overcome public health interventions and rising population immunity. Here, by examining patterns of synonymous and non-synonymous mutations that have accumulated in SARS-CoV-2 genomes since the pandemic began, we find that the emergence of these three "501Y lineages" coincided with a major global shift in the selective forces acting on various SARS-CoV-2 genes. Following their emergence, the adaptive evolution of 501Y lineage viruses has involved repeated selectively favored convergent mutations at 35 genome sites, mutations we refer to as the 501Y meta-signature. The ongoing convergence of viruses in many other lineages on this meta-signature suggests that it includes multiple mutation combinations capable of promoting the persistence of diverse SARS-CoV-2 lineages in the face of mounting host immune recognition.

Analysing the impact of the two most common SARS-CoV-2 nucleocapsid protein variants on interactions with membrane protein in silico

As the body of scientific research focusing on the severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 continues to grow, several mutations have been reported as very common across the globe. In this study, we analysed the SARS-CoV-2 nucleocapsid protein (N protein) with respect to the widely observed 28881-28883 GGG to AAC variant. One of the major functions of the SARS-CoV-2 nucleocapsid protein is virion packaging through its interactions with the membrane protein (M protein). Our goal was to investigate, using in silico studies, the interaction between the mutant nucleocapsid protein and the M protein and how it differed from that of wild type N-M protein interaction. The results showed significant differences in interactions between the two. The mutant protein was predicted to form 3 salt bridges with the M protein, while the wild type only formed 2. The mutant protein was also predicted to display less temperature sensitivity than its wild type counterpart.

Phylogenetic reconstruction of the initial stages of the spread of the SARS-CoV-2 virus in the Eurasian and American continents by analyzing genomic data

Samples from complete genomes of SARS-CoV-2 isolated during the first wave (December 2019–July 2020) of the global COVID-19 pandemic from 21 countries (Asia, Europe, Middle East and America) around the world, were analyzed using the phylogenetic method with molecular clock dating. Results showed that the first cases of COVID-19 in the human population appeared in the period between July and November 2019 in China. The spread of the virus into other countries of the world began in the autumn of 2019. In mid-February 2020, the virus appeared in all the countries we analyzed. During this time, the global population of SARS-CoV-2 was characterized by low levels of the genetic polymorphism, making it difficult to accurately assess the pathways of infection. The rate of evolution of the coding region of the SARS-CoV-2 genome equal to 7.3 × 10⁻⁴ (5.95 × 10⁻⁴–8.68 × 10⁻⁴) nucleotide substitutions per site per year is comparable to those of other human RNA viruses (Measles morbillivirus, Rubella virus, Enterovirus C). SARS-CoV-2 was separated from its known close relative, the bat coronavirus RaTG13 of the genus Betacoronavirus, approximately 15–43 years ago (the end of the 20th century).

Multiple Roles of SARS-CoV-2 N Protein Facilitated by Proteoform-Specific Interactions with RNA, Host Proteins, and Convalescent Antibodies

The SARS-CoV-2 nucleocapsid (N) protein is a highly immunogenic viral protein that plays essential roles in replication and virion assembly. Here, using native mass spectrometry, we show that dimers are the functional unit of ribonucleoprotein assembly and that N protein binds RNA with a preference for GGG motifs, a common motif in coronavirus packaging signals. Unexpectedly, proteolytic processing of N protein resulted in the formation of additional proteoforms. The N-terminal proteoforms bind RNA, with the same preference for GGG motifs, and bind to cyclophilin A, an interaction which can be abolished by approved immunosuppressant cyclosporin A. Furthermore, N proteoforms showed significantly different interactions with IgM, IgG, and IgA antibodies from convalescent plasma. Notably, the C-terminal proteoform exhibited a heightened interaction with convalescent antibodies, suggesting the antigenic epitope is localized to the C-terminus. Overall, the different interactions of N proteoforms highlight potential avenues for therapeutic intervention and identify a stable and immunogenic proteoform as a possible candidate for immune-directed therapies.

Accelerating COVID-19 Research Using Molecular Dynamics Simulation

The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.

Immunological mechanisms of vaccine-induced protection against COVID-19 in humans

Most COVID-19 vaccines are designed to elicit immune responses, ideally neutralizing antibodies (NAbs), against the SARS-CoV-2 spike protein. Several vaccines, including mRNA, adenoviral-vectored, protein subunit and whole-cell inactivated virus vaccines, have now reported efficacy in phase III trials and have received emergency approval in many countries. The two mRNA vaccines approved to date show efficacy even after only one dose, when non-NAbs and moderate T helper 1 cell responses are detectable, but almost no NAbs. After a single dose, the adenovirus vaccines elicit polyfunctional antibodies that are capable of mediating virus neutralization and of driving other antibody-dependent effector functions, as well as potent T cell responses. These data suggest that protection may require low levels of NAbs and might involve other immune effector mechanisms including non-NAbs, T cells and innate immune mechanisms. Identifying the mechanisms of protection as well as correlates of protection is crucially important to inform further vaccine development and guide the use of licensed COVID-19 vaccines worldwide.

The emergence and ongoing convergent evolution of the N501Y lineages coincides with a major global shift in the SARS-CoV-2 selective landscape

The emergence and rapid rise in prevalence of three independent SARS-CoV-2 "501Y lineages", B.1.1.7, B.1.351 and P.1, in the last three months of 2020 prompted renewed concerns about the evolutionary capacity of SARS-CoV-2 to adapt to both rising population immunity, and public health interventions such as vaccines and social distancing. Viruses giving rise to the different 501Y lineages have, presumably under intense natural selection following a shift in host environment, independently acquired multiple unique and convergent mutations. As a consequence, all have gained epidemiological and immunological properties that will likely complicate the control of COVID-19. Here, by examining patterns of mutations that arose in SARSCoV-2 genomes during the pandemic we find evidence of a major change in the selective forces acting on various SARS-CoV-2 genes and gene segments (such as S, nsp2 and nsp6), that likely coincided with the emergence of the 501Y lineages. In addition to involving continuing sequence diversification, we find evidence that a significant portion of the ongoing adaptive evolution of the 501Y lineages also involves further convergence between the lineages. Our findings highlight the importance of monitoring how members of these known 501Y lineages, and others still undiscovered, are convergently evolving similar strategies to ensure their persistence in the face of mounting infection and vaccine induced host immune recognition.

Temporal landscape of mutational frequencies in SARS-CoV-2 genomes of Bangladesh: possible implications from the ongoing outbreak in Bangladesh

Along with intrinsic evolution, adaptation to selective pressure in new environments might have resulted in the circulatory SARS-CoV-2 strains in response to the geoenvironmental conditions of a country and the demographic profile of its population. With this target, the current study traced the evolutionary route and mutational frequency of 198 Bangladesh-originated SARS-CoV-2 genomic sequences available in the GISAID platform over a period of 13 weeks as of 14 July 2020. The analyses were performed using MEGA X, Swiss Model Repository, Virus Pathogen Resource and Jalview visualization. Our analysis identified that majority of the circulating strains strikingly differ from both the reference genome and the first sequenced genome from Bangladesh. Mutations in nonspecific proteins (NSP2-3, NSP-12(RdRp), NSP-13(Helicase)), S-Spike, ORF3a, and N-Nucleocapsid protein were common in the circulating strains with varying degrees and the most unique mutations (UM) were found in NSP3 (UM-18). But no or limited changes were observed in NSP9, NSP11, Envelope protein (E) and accessory factors (NSP7a, ORF 6, ORF7b) suggesting the possible conserved functions of those proteins in SARS-CoV-2 propagation. However, along with D614G mutation, more than 20 different mutations in the Spike protein were detected basically in the S2 domain. Besides, mutations in SR-rich region of N protein and P323L in RDRP were also present. However, the mutation accumulation showed a significant association (p = 0.003) with sex and age of the COVID-19-positive cases. So, identification of these mutational accumulation patterns may greatly facilitate vaccine development deciphering the age and the sex-dependent differential susceptibility to COVID-19.

The First Molecular Characterization of Serbian SARS-CoV-2 Isolates From a Unique Early Second Wave in Europe

March 6, 2020 is considered as the official date of the beginning of the COVID-19 epidemic in Serbia. In late spring and early summer 2020, Europe recorded a decline in the rate of SARS-CoV-2 infection and subsiding of the first wave. This trend lasted until the fall, when the second wave of the epidemic began to appear. Unlike the rest of Europe, Serbia was hit by the second wave of the epidemic a few months earlier. Already in June 2020, newly confirmed cases had risen exponentially. As the COVID-19 pandemic is the first pandemic in which there has been instant sharing of genomic information on isolates around the world, the aim of this study was to analyze whole SARS-CoV-2 viral genomes from Serbia, to identify circulating variants/clade/lineages, and to explore site-specific mutational patterns in the unique early second wave of the European epidemic. This analysis of Serbian isolates represents the first publication from Balkan countries, which demonstrates the importance of specificities of local transmission especially when preventive measures differ among countries. One hundred forty-eight different genome variants among 41 Serbian isolates were detected in this study. One unique and seven extremely rare mutations were identified, with locally specific continuous dominance of the 20D clade. At the same time, amino acid substitutions of newly identified variants of concern were found in our isolates from October 2020. Future research should be focused on functional characterization of novel mutations in order to understand the exact role of these variations.

Introduction of ORF3a-Q57H SARS-CoV-2 Variant Causing Fourth Epidemic Wave of COVID-19, Hong Kong, China

We describe an introduction of clade GH severe acute respiratory syndrome coronavirus 2 causing a fourth wave of coronavirus disease in Hong Kong. The virus has an ORF3a-Q57H mutation, causing truncation of ORF3b. This virus evades induction of cytokine, chemokine, and interferon-stimulated gene expression in primary human respiratory cells.

Potential transmission chains of variant B.1.1.7 and co-mutations of SARS-CoV-2

The presence of SARS-CoV-2 mutants, including the emerging variant B.1.1.7, has raised great concerns in terms of pathogenesis, transmission, and immune escape. Characterizing SARS-CoV-2 mutations, evolution, and effects on infectivity and pathogenicity is crucial to the design of antibody therapies and surveillance strategies. Here, we analyzed 454,443 SARS-CoV-2 spike genes/proteins and 14,427 whole-genome sequences. We demonstrated that the early variant B.1.1.7 may not have evolved spontaneously in the United Kingdom or within human populations. Our extensive analyses suggested that Canidae, Mustelidae or Felidae, especially the Canidae family (for example, dog) could be a possible host of the direct progenitor of variant B.1.1.7. An alternative hypothesis is that the variant was simply yet to be sampled. Notably, the SARS-CoV-2 whole-genome represents a large number of potential co-mutations. In addition, we used an experimental SARS-CoV-2 reporter replicon system to introduce the dominant co-mutations NSP12_c14408t, 5'UTR_c241t, and NSP3_c3037t into the viral genome, and to monitor the effect of the mutations on viral replication. Our experimental results demonstrated that the co-mutations significantly attenuated the viral replication. The study provides valuable clues for discovering the transmission chains of variant B.1.1.7 and understanding the evolutionary process of SARS-CoV-2.

Mutational Asymmetries in the SARS-CoV-2 Genome May Lead to Increased Hydrophobicity of Virus Proteins

The genomic diversity of SARS-CoV-2 has been a focus during the ongoing COVID-19 pandemic. Here, we analyzed the distribution and character of emerging mutations in a data set comprising more than 95,000 virus genomes covering eight major SARS-CoV-2 lineages in the GISAID database, including genotypes arising during COVID-19 therapy. Globally, the C>U transitions and G>U transversions were the most represented mutations, accounting for the majority of single-nucleotide variations. Mutational spectra were not influenced by the time the virus had been circulating in its host or medical treatment. At the amino acid level, we observed about a 2-fold excess of substitutions in favor of hydrophobic amino acids over the reverse. However, most mutations constituting variants of interests of the S-protein (spike) lead to hydrophilic amino acids, counteracting the global trend. The C>U and G>U substitutions altered codons towards increased amino acid hydrophobicity values in more than 80% of cases. The bias is explained by the existing differences in the codon composition for amino acids bearing contrasting biochemical properties. Mutation asymmetries apparently influence the biochemical features of SARS CoV-2 proteins, which may impact protein-protein interactions, fusion of viral and cellular membranes, and virion assembly.

Genetic Diversity of SARS-CoV-2 over a One-Year Period of the COVID-19 Pandemic: A Global Perspective

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of coronavirus disease in 2019 (COVID-19). Genome surveillance is a key method to track the spread of SARS-CoV-2 variants. Genetic diversity and evolution of SARS-CoV-2 were analyzed based on 260,673 whole-genome sequences, which were sampled from 62 countries between 24 December 2019 and 12 January 2021. We found that amino acid (AA) substitutions were observed in all SARS-CoV-2 proteins, and the top six proteins with the highest substitution rates were ORF10, nucleocapsid, ORF3a, spike glycoprotein, RNA-dependent RNA polymerase, and ORF8. Among 25,629 amino acid substitutions at 8484 polymorphic sites across the coding region of the SARS-CoV-2 genome, the D614G (93.88%) variant in spike and the P323L (93.74%) variant in RNA-dependent RNA polymerase were the dominant variants on six continents. As of January 2021, the genomic sequences of SARS-CoV-2 could be divided into at least 12 different clades. Distributions of SARS-CoV-2 clades were featured with temporal and geographical dynamics on six continents. Overall, this large-scale analysis provides a detailed mapping of SARS-CoV-2 variants in different geographic areas at different time points, highlighting the importance of evaluating highly prevalent variants in the development of SARS-CoV-2 antiviral drugs and vaccines.

An Overview of Spike Surface Glycoprotein in Severe Acute Respiratory Syndrome-Coronavirus

The novel coronavirus originated in December 2019 in Hubei, China. This contagious disease named as COVID-19 resulted in a massive expansion within 6 months by spreading to more than 213 countries. Despite the availability of antiviral drugs for the treatment of various viral infections, it was concluded by the WHO that there is no medicine to treat novel CoV, SARS-CoV-2. It has been confirmed that SARS-COV-2 is the most highly virulent human coronavirus and occupies the third position following SARS and MERS with the highest mortality rate. The genetic assembly of SARS-CoV-2 is segmented into structural and non-structural proteins, of which two-thirds of the viral genome encodes non-structural proteins and the remaining genome encodes structural proteins. The most predominant structural proteins that make up SARS-CoV-2 include spike surface glycoproteins (S), membrane proteins (M), envelope proteins (E), and nucleocapsid proteins (N). This review will focus on one of the four major structural proteins in the CoV assembly, the spike, which is involved in host cell recognition and the fusion process. The monomer disintegrates into S1 and S2 subunits with the S1 domain necessitating binding of the virus to its host cell receptor and the S2 domain mediating the viral fusion. On viral infection by the host, the S protein is further cleaved by the protease enzyme to two major subdomains S1/S2. Spike is proven to be an interesting target for developing vaccines and in particular, the RBD-single chain dimer has shown initial success. The availability of small molecules and peptidic inhibitors for host cell receptors is briefly discussed. The development of new molecules and therapeutic druggable targets for SARS-CoV-2 is of global importance. Attacking the virus employing multiple targets and strategies is the best way to inhibit the virus. This article will appeal to researchers in understanding the structural and biological aspects of the S protein in the field of drug design and discovery.

Genome composition and genetic characterization of SARS-CoV-2

SARS-CoV-2 is a type of Betacoronaviruses responsible for COVID-19 pandemic disease, with more than 1.745 million fatalities globally as of December-2020. Genetically, it is considered the second largest genome of all RNA viruses with a 5' cap and 3' poly-A tail. Phylogenetic analyses of coronaviruses reveal that SARS-CoV-2 is genetically closely related to the Bat-SARS Like-Corona virus (Bat-SL-Cov) with 96% whole-genome identity. SARS-CoV-2 genome consists of 15 ORFs coded into 29 proteins. At the 5' terminal of the genome, we have ORF1ab and ORF1a, which encode the 1ab and 1a polypeptides that are proteolytically cleaved into 16 different nonstructural proteins (NSPs). The 3' terminal of the genome represents four structural (spike, envelope, matrix, and nucleocapsid) and nine accessory (3a, 3b, 6, 7a, 7b, 8b, 9a, 9b, and orf10) proteins. As the number of COVID-19 patients increases dramatically worldwide, there is an urgent need to find a quick and sensitive diagnostic tool for controlling the outbreak of SARS-CoV-2 in the community. Today, molecular testing methods utilizing viral genetic material (e.g., PCR) represent the crucial diagnostic tool for the SARS-CoV-2 virus despite its low sensitivity in the early stage of viral infection. This review summarizes the genome composition and genetic characterization of the SARS-CoV-2.

Comparative Genomics and Integrated Network Approach Unveiled Undirected Phylogeny Patterns, Co-mutational Hot Spots, Functional Cross Talk, and Regulatory Interactions in SARS-CoV-2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in 92 million cases in a span of 1 year. The study focuses on understanding population-specific variations attributing its high rate of infections in specific geographical regions particularly in the United States. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d, and e (subtypes e1 and e2). Clade d and subclade e2 were found exclusively comprised of U.S. strains. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2, and Nsp6. Our analysis revealed that only 67.46% of single nucleotide polymorphism (SNP) mutations were at the amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except for 6 strains which were marked as ancestral type, whereas co-mutation (P409L and Y446C) in Nsp13 were found in 64 genomes from the United States highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of spike proteins with angiotensin-converting enzyme 2 (ACE2), but it also showed better interaction with the TMPRSS2 receptor contributing to high transmissibility among U.S. strains. We also found host proteins, MYO5A, MYO5B, and MYO5C, that had maximum interaction with viral proteins (nucleocapsid [N], spike [S], and membrane [M] proteins). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for coronavirus disease 2019 (COVID-19) treatment. The functional annotations of the host-pathogen interaction (HPI) network were found to be closely associated with hypoxia and thrombotic conditions, confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 and N conferring the ability of SARS-CoV-2 to enter and trigger zinc antiviral protein (ZAP) activity inside the host cell.

IMPORTANCE In the current study, we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions especially in U.S. strains. Compositional structural biology results suggested that mutations have a balance of opposing forces affecting pathogenicity suggesting that only a few mutations are effective at the translation level. Novel HPI analysis and CpG predictions elucidate the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population-specific variations attributing a high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies.