GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes.

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying variants of concern (VOC). Viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host single nucleotide variations (iSNVs). Analysing 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.

Genetic Diversity, Antimicrobial Resistance Pattern, and Biofilm Formation in Klebsiella pneumoniae Isolated from Patients with Coronavirus Disease 2019 (COVID-19) and Ventilator-Associated Pneumonia.

INTRODUCTION: Patients with acute respiratory distress syndrome caused by coronavirus disease 2019 (COVID-19) are at risk for superadded infections, especially infections caused by multidrug resistant (MDR) pathogens. Before the COVID-19 pandemic, the prevalence of MDR infections, including infections caused by MDR Klebsiella pneumoniae (K. pneumoniae), was very high in Iran. This study is aimed at assessing the genetic diversity, antimicrobial resistance pattern, and biofilm formation in K. pneumoniae isolates obtained from patients with COVID-19 and ventilator-associated pneumonia (VAP) hospitalized in an intensive care unit (ICU) in Iran. METHODS: In this cross-sectional study, seventy K. pneumoniae isolates were obtained from seventy patients with COVID-19 hospitalized in the ICU of Shahid Beheshti hospital, Kashan, Iran, from May to September, 2020. K. pneumoniae was detected through the ureD gene. Antimicrobial susceptibility testing was done using the Kirby-Bauer disc diffusion method, and biofilm was detected using the microtiter plate assay method. Genetic diversity was also analyzed through polymerase chain reaction based on enterobacterial repetitive intergenic consensus (ERIC-PCR). The BioNumerics software (v. 8.0, Applied Maths, Belgium) was used for analyzing the data and drawing dendrogram and minimum spanning tree. Findings. K. pneumoniae isolates had varying levels of resistance to antibiotics meropenem (80.4%), cefepime-aztreonam-piperacillin/tazobactam (70%), tobramycin (61.4%), ciprofloxacin (57.7%), gentamicin (55.7%), and imipenem (50%). Around 77.14% of isolates were MDR, and 42.8% of them formed biofilm. Genetic diversity analysis revealed 28 genotypes (E1-E28) and 74.28% of isolates were grouped into ten clusters (i.e., clusters A-J). Clusters were further categorized into three major clusters, i.e., clusters E, H, and J. Antimicrobial resistance to meropenem, tobramycin, gentamicin, and ciprofloxacin in cluster J was significantly higher than cluster H, denoting significant relationship between ERIC clusters and antimicrobial resistance. However, there was no significant difference among major clusters E, H, and J respecting biofilm formation. CONCLUSION: K. pneumoniae isolates obtained from patients with COVID-19 have high antimicrobial resistance, and 44.2% of them have genetic similarity and can be clustered in three major clusters. There is a significant difference among clusters respecting antimicrobial resistance.

A critical analysis of SARS-CoV-2 (COVID-19) complexities, emerging variants, and therapeutic interventions and vaccination strategies.

Coronavirus is a family of viruses that can cause diseases such as the common cold, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS). The universal outbreak of coronavirus disease 2019 (COVID-19) caused by SARS coronaviruses 2 (SARS-CoV-2) has become a global pandemic. The ß-Coronaviruses, which caused SARS-CoV-2 (COVID-19), have spread in more than 213 countries, infected over 81 million people, and caused more than 1.79 million deaths. COVID-19 symptoms vary from mild fever, flu to severe pneumonia in severely ill patients. Difficult breathing, acute respiratory distress syndrome (ARDS), acute kidney disease, liver damage, and multi-organ failure ultimately lead to death. Researchers are working on different pre-clinical and clinical trials to prevent this deadly pandemic by developing new vaccines. Along with vaccines, therapeutic intervention is an integral part of healthcare response to address the ongoing threat posed by COVID-19. Despite the global efforts to understand and fight against COVID-19, many challenges need to be addressed. This article summarizes the current pandemic, different strains of SARS-CoV-2, etiology, complexities, surviving medications of COVID-19, and so far, vaccination for the treatment of COVID-19.

Efficacy of mRNA, adenoviral vector, and perfusion protein COVID-19 vaccines.

Coronavirus disease 2019 (COVID-19) has a devastating impact on global populations triggered by a highly infectious viral sickness, produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The third major cause of mortality in the United States, following heart disease and cancer in 2020, was undoubtedly COVID-19. The centers for disease control and prevention (CDC) and the world health organization (WHO) separately developed a categorization system for differentiating new strains of SARS-CoV-2 into variants of concern (VoCs) and variants of interest (VoIs) with the continuing development of various strains SARS-CoV-2. By December 2021, five of the SARS-CoV-2 VoCs were discovered from the onset of the pandemic depending on the latest epidemiologic report by the WHO: Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). Mutations in the receptor-binding domain (RBD) and n-terminal domain (NTD) have been found throughout all five identified VoCs. All strains other than the delta mutant are often found with the N501Y mutation situated on the RBD, resulting in higher binding between the spike protein and angiotensin-converting enzyme 2 (ACE2) receptors, enhanced viral adhesion, and following the entrance to host cells. The introduction of these new strains of SRAS-CoV-2 is likely to overcome the remarkable achievements gained in restricting this viral disease to the point where it is presented with remarkable vaccine developments against COVID-19 and strong worldwide mass immunization initiatives. Throughout this literature review, the effectiveness of current COVID-19 vaccines for managing and prohibiting SARS-CoV-2 strains is thoroughly described.

SARS-CoV-2 genetic variations associated with COVID-19 pathogenicity.

In this study, we performed genome-wide association analyses on SARS-CoV-2 genomes to identify genetic mutations associated with pre-symptomatic/asymptomatic COVID-19 cases. Various potential covariates and confounding factors of COVID-19 severity, including patient age, gender and country, as well as virus phylogenetic relatedness were adjusted for. In total, 3021 full-length genomes of SARS-CoV-2 generated from original clinical samples and whose patient status could be determined conclusively as either 'pre-symptomatic/asymptomatic' or 'symptomatic' were retrieved from the GISAID database. We found that the mutation 11 083G>T, located in the coding region of non-structural protein 6, is significantly associated with asymptomatic COVID-19. Patient age is positively correlated with symptomatic infection, while gender is not significantly correlated with the development of the disease. We also found that the effects of the mutation, patient age and gender do not vary significantly among countries, although each country appears to have varying baseline chances of COVID-19 symptom development.

Genetic drift in the genome of SARS COV-2 and its global health concern.

The outbreak of the current coronavirus disease (COVID-19) occurred in late 2019 and quickly spread all over the world. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) belongs to a genetically diverse group that mutates continuously leading to the emergence of multiple variants. Although a few antiviral agents and anti-inflammatory medicines are available, thousands of individuals have passed away due to emergence of new viral variants. Thus, proper surveillance of the SARS-CoV-2 genome is needed for the rapid identification of developing mutations over time, which are of the major concern if they occur specifically in the surface spike proteins of the virus (neutralizing analyte). This article reviews the potential mutations acquired by the SARS-CoV2 since the pandemic began and their significant impact on the neutralizing efficiency of vaccines and validity of the diagnostic assays.

G6PD distribution in sub-Saharan Africa and potential risks of using chloroquine/hydroxychloroquine based treatments for COVID-19.

Chloroquine/hydroxychloroquine have been proposed as potential treatments for COVID-19. These drugs have warning labels for use in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Analysis of whole genome sequence data of 458 individuals from sub-Saharan Africa showed significant G6PD variation across the continent. We identified nine variants, of which four are potentially deleterious to G6PD function, and one (rs1050828) that is known to cause G6PD deficiency. We supplemented data for the rs1050828 variant with genotype array data from over 11,000 Africans. Although this variant is common in Africans overall, large allele frequency differences exist between sub-populations. African sub-populations in the same country can show significant differences in allele frequency (e.g. 16.0% in Tsonga vs 0.8% in Xhosa, both in South Africa, p = 2.4 × 10-3). The high prevalence of variants in the G6PD gene found in this analysis suggests that it may be a significant interaction factor in clinical trials of chloroquine and hydroxychloroquine for treatment of COVID-19 in Africans.

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues.

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types.

Identification of genotypic variants and its proteomic mutations of Brazilian SARS-CoV-2 isolates.

The second wave of COVID-19 caused by severe acute respiratory syndrome virus (SARS-CoV-2) is rapidly spreading over the world. Mechanisms behind the flee from current antivirals are still unclear due to the continuous occurrence of SARS-CoV-2 genetic variants. Brazil is the world's second-most COVID-19 affected country. In the present study, we identified the genomic and proteomic variants of Brazilian SARS-CoV-2 isolates. We identified 16 different genotypic variants were found among the 27 isolates. The genotypes of three isolates such as Bra/1236/2021 (G15), Bra/MASP2C844R2/2020 (G11), and Bra/RJ-DCVN5/2020 (G9) have a unique mutant in NSP4 (S184N), 2'O-Mutase (R216N), membrane protein (A2V) and Envelope protein (V5A). A mutation in RdRp of SARS-CoV-2, particularly the change of Pro-to Leu-at 323 resulted in the stabilization of the structure in BRA/CD1739-P4/2020. NSP4, NSP5 protein mutants are more virulent in genotype 15 and 16. A fast protein folding rate changes the structural stability and leads to escape for current antivirals. Thus, our findings help researchers to develop the best potent antivirals based on the new mutant of Brazilian isolates.

Identification of hub genes and molecular subtypes in COVID-19 based on WGCNA.

OBJECTIVE: The heterogeneity of clinical manifestations and mortality rates in Coronavirus disease 2019 (COVID-19) patients may be related to the existence of molecular subtypes in COVID-19. To improve current management, it is essential to find the hub genes and pathways associated with different COVID-19 subtypes. MATERIALS AND METHODS: The whole-genome sequencing information (GSE156063, GSE163151) of nasopharyngeal swabs from normal subjects and COVID-19 patients were downloaded from the Gene Expression Omnibus (GEO) database. The molecular subtypes of patients with COVID-19 were classified using the "consistent clustering" method, and the specific genes associated with each subtype were found. Differentially expressed genes (DEGs) were screened between normal subjects and COVID-19 patients; the Weighted gene co-expression network analysis (WGCNA) method was used to find the key module genes of COVID-19 patients. Subtype-specific, differentially expressed and module-related genes were collected and intersected. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out and protein-protein interaction (PPI) networks were generated. The pathways enriched in COVID-19 subtypes were analyzed by gene set variation analysis (GSVA). RESULTS: Patients with COVID-19 were divided into three subtypes, and there was no significant difference in gender and age distribution between subtypes. 82 differential gene pathways were screened between Subtypes I and II, 131 differential gene pathways were screened between Subtypes I and III, and 107 differential gene pathways were screened between Subtypes II and III. Finally, 44 differentially expressed key genes were screened, including 11 hub genes (RSAD2, IFIT1, MX1, OAS1, OAS2, BST2, IFI27, IFI35, IFI6, IFITM3, STAT2). CONCLUSIONS: There are significant differences in gene activation and pathway enrichment among different molecular subtypes of COVID-19, which may account for the heterogeneity in clinical presentation and the prognosis of patients.

Wave-wise comparative genomic study for revealing the complete scenario and dynamic nature of COVID-19 pandemic in Bangladesh.

As the COVID-19 pandemic continues to ravage across the globe and take millions of lives and like many parts of the world, the second wave of the pandemic hit Bangladesh, this study aimed at understanding its causative agent, SARS-CoV-2 at the genomic and proteomic level and provide precious insights about the pathogenesis, evolution, strengths and weaknesses of the virus. As of Mid-June 2021, over 1500 SARS-CoV-2 genomesequences have been deposited in the GISAID database from Bangladesh which were extracted and categorized into two waves. By analyzing these genome sequences, it was discovered that the wave-2 samples had a significantly greater average rate of mutation/sample (30.79%) than the wave-1 samples (12.32%). Wave-2 samples also had a higher frequency of deletion, and transversion events. During the first wave, the GR clade was the most predominant but it was replaced by the GH clade in the latter wave. The B.1.1.25 variant showed the highest frequency in wave-1 while in case of wave-2, the B.1.351.3 variant, was the most common one. A notable presence of the delta variant, which is currently at the center of concern, was also observed. Comparison of the Spike protein found in the reference and the 3 most common lineages found in Bangladesh namely, B.1.1.7, B.1.351, B.1.617 in terms of their ability to form stable complexes with ACE2 receptor revealed that B.1.617 had the potential to be more transmissible than others. Importantly, no indigenous variants have been detected so far which implies that the successful prevention of import of foreign variants can diminish the outbreak in the country.

Genomic Characterization of Diverse Bat Coronavirus HKU10 in Hipposideros Bats.

Bats have been identified as natural reservoirs of a variety of coronaviruses. They harbor at least 19 of the 33 defined species of alpha- and betacoronaviruses. Previously, the bat coronavirus HKU10 was found in two bat species of different suborders, Rousettus leschenaultia and Hipposideros pomona, in south China. However, its geographic distribution and evolution history are not fully investigated. Here, we screened this viral species by a nested reverse transcriptase PCR in our archived samples collected over 10 years from 25 provinces of China and one province of Laos. From 8004 bat fecal samples, 26 were found to be positive for bat coronavirus HKU10 (BtCoV HKU10). New habitats of BtCoV HKU10 were found in the Yunnan, Guangxi, and Hainan Provinces of China, and Louang Namtha Province in Laos. In addition to H. pomona, BtCoV HKU10 variants were found circulating in Aselliscus stoliczkanus and Hipposideros larvatus. We sequenced full-length genomes of 17 newly discovered BtCoV HKU10 strains and compared them with previously published sequences. Our results revealed a much higher genetic diversity of BtCoV HKU10, particularly in spike genes and accessory genes. Besides the two previously reported lineages, we found six novel lineages in their new habitats, three of which were located in Yunnan province. The genotypes of these viruses are closely related to sampling locations based on polyproteins, and correlated to bat species based on spike genes. Combining phylogenetic analysis, selective pressure, and molecular-clock calculation, we demonstrated that Yunnan bats harbor a gene pool of BtCoV HKU10, with H. pomona as a natural reservoir. The cell tropism test using spike-pseudotyped lentivirus system showed that BtCoV HKU10 could enter cells from human and bat, suggesting a potential interspecies spillover. Continuous studies on these bat coronaviruses will expand our understanding of the evolution and genetic diversity of coronaviruses, and provide a prewarning of potential zoonotic diseases from bats.

ACE Gene Variants Rise the Risk of Severe COVID-19 in Patients With Hypertension, Dyslipidemia or Diabetes: A Spanish Pilot Study.

Coronavirus disease 19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to scale and threaten human health and public safety. It is essential to identify those risk factors that lead to a poor prognosis of the disease. A predisposing host genetic background could be one of these factors that explain the interindividual variability to COVID-19 severity. Thus, we have studied whether the rs4341 and rs4343 polymorphisms of the angiotensin converting enzyme (ACE) gene, key regulator of the renin-aldosterone-angiotensin system (RAAS), could explain the different outcomes of 128 COVID-19 patients with diverse degree of severity (33 asymptomatic or mildly symptomatic, 66 hospitalized in the general ward, and 29 admitted to the ICU). We found that G allele of rs4341 and rs4343 was associated with severe COVID-19 in hypertensive patients, independently of gender (p<0.05). G-carrier genotypes of both polymorphisms were also associated with higher mortality (p< 0.05) and higher severity of COVID-19 in dyslipidemic (p<0.05) and type 2 diabetic patients (p< 0.01). The association of G alleles with disease severity was adjusted for age, sex, BMI and number of comorbidities, suggesting that both the metabolic comorbidities and the G allele act synergistically on COVID-19 outcome. Although we did not find a direct association between serum ACE levels and COVID-19 severity, we found higher levels of ACE in the serum of patients with the GG genotype of rs4341 and rs4343 (p<0.05), what could explain the higher susceptibility to develop severe forms of the disease in patients with the GG genotype, in addition to hypertension and dyslipidemia. In conclusion, our preliminary study suggests that the G-containing genotypes of rs4341 and rs4343 confer an additional risk of adverse COVID-19 prognosis. Thus, rs4341 and rs4343 polymorphisms of ACE could be predictive markers of severity of COVID-19 in those patients with hypertension, dyslipidemia or diabetes. The knowledge of these genetic data could contribute to precision management of SARS-CoV-2 infected patients when admitted to hospital.

ACoRE: Accurate SARS-CoV-2 genome reconstruction for the characterization of intra-host and inter-host viral diversity in clinical samples and for the evaluation of re-infections.

Sequencing the SARS-CoV-2 genome from clinical samples can be challenging, especially in specimens with low viral titer. Here we report Accurate SARS-CoV-2 genome Reconstruction (ACoRE), an amplicon-based viral genome sequencing workflow for the complete and accurate reconstruction of SARS-CoV-2 sequences from clinical samples, including suboptimal ones that would usually be excluded even if unique and irreplaceable. The protocol was optimized to improve flexibility and the combination of technical replicates was established as the central strategy to achieve accurate analysis of low-titer/suboptimal samples. We demonstrated the utility of the approach by achieving complete genome reconstruction and the identification of false-positive variants in >170 clinical samples, thus avoiding the generation of inaccurate and/or incomplete sequences. Most importantly, ACoRE was crucial to identify the correct viral strain responsible of a relapse case, that would be otherwise mis-classified as a re-infection due to missing or incorrect variant identification by a standard workflow.

Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: an endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations.

Accumulation of mutations within the genome is the primary driving force in viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility, and antigenic shifts to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we carried out a genome-wide analysis of circulating SARS-CoV-2 strains to detect the emergence of novel co-existing mutations and trace their geographical distribution within India. Comprehensive analysis of whole genome sequences of 837 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 18 of which were unique to India. Novel mutations were observed in the S glycoprotein (6/33), NSP3 (5/33), RdRp/NSP12 (4/33), NSP2 (2/33), and N (1/33). Non-synonymous mutations were found to be 3.07 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on their co-existing mutations. Phylogenetic analysis revealed that the representative strains of each group were divided into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. The A2a clade was found to be dominant in India (71.34%), followed by A3 (23.29%) and B (5.36%), but a heterogeneous distribution was observed among various geographical regions. The A2a clade was highly predominant in East India, Western India, and Central India, whereas the A2a and A3 clades were nearly equal in prevalence in South and North India. This study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations will pave the way for vaccine formulation and the design of antiviral drugs.

Targeted Hybridization Capture of SARS-CoV-2 and Metagenomics Enables Genetic Variant Discovery and Nasal Microbiome Insights.

The emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic variants that may alter viral fitness highlights the urgency of widespread next-generation sequencing (NGS) surveillance. To profile genetic variants of the entire SARS-CoV-2 genome, we developed and clinically validated a hybridization capture SARS-CoV-2 NGS assay, integrating novel methods for panel design using double-stranded DNA (dsDNA) biotin-labeled probes, and built accompanying software. This test is the first hybrid capture-based NGS assay given Food and Drug Administration (FDA) emergency use authorization for detection of the SARS-CoV-2 virus. The positive and negative percent agreement (PPA and NPA, respectively) were defined in comparison to the results for an orthogonal real-time reverse transcription polymerase chain reaction (RT-PCR) assay (PPA and NPA, 96.7 and 100%, respectively). The limit of detection was established to be 800 copies/ml with an average fold enrichment of 46,791. Furthermore, utilizing the research-use-only analysis to profile the variants, we identified 55 novel mutations, including 11 in the functionally important spike protein. Finally, we profiled the full nasopharyngeal microbiome using metagenomics and found overrepresentation of 7 taxa and evidence of macrolide resistance in SARS-CoV-2-positive patients. This hybrid capture NGS assay, coupled with optimized software, is a powerful approach to detect and comprehensively map SARS-CoV-2 genetic variants for tracking viral evolution and guiding vaccine updates. IMPORTANCE This is the first FDA emergency-use-authorized hybridization capture-based next-generation sequencing (NGS) assay to detect the SARS-CoV-2 genome. Viral metagenomics and the novel hybrid capture NGS-based assay, along with its research-use-only analysis, can provide important genetic insights into SARS-CoV-2 and other emerging pathogens and improve surveillance and early detection, potentially preventing or mitigating new outbreaks. Better understanding of the continuously evolving SARS-CoV-2 viral genome and the impact of genetic variants may provide individual risk stratification, precision therapeutic options, improved molecular diagnostics, and population-based therapeutic solutions.

Data-driven identification of SARS-CoV-2 subpopulations using PhenoGraph and binary-coded genomic data.

For epidemic prevention and control, the identification of SARS-CoV-2 subpopulations sharing similar micro-epidemiological patterns and evolutionary histories is necessary for a more targeted investigation into the links among COVID-19 outbreaks caused by SARS-CoV-2 with similar genetic backgrounds. Genomic sequencing analysis has demonstrated the ability to uncover viral genetic diversity. However, an objective analysis is necessary for the identification of SARS-CoV-2 subpopulations. Herein, we detected all the mutations in 186 682 SARS-CoV-2 isolates. We found that the GC content of the SARS-CoV-2 genome had evolved to be lower, which may be conducive to viral spread, and the frameshift mutation was rare in the global population. Next, we encoded the genomic mutations in binary form and used an unsupervised learning classifier, namely PhenoGraph, to classify this information. Consequently, PhenoGraph successfully identified 303 SARS-CoV-2 subpopulations, and we found that the PhenoGraph classification was consistent with, but more detailed and precise than the known GISAID clades (S, L, V, G, GH, GR, GV and O). By the change trend analysis, we found that the growth rate of SARS-CoV-2 diversity has slowed down significantly. We also analyzed the temporal, spatial and phylogenetic relationships among the subpopulations and revealed the evolutionary trajectory of SARS-CoV-2 to a certain extent. Hence, our results provide a better understanding of the patterns and trends in the genomic evolution and epidemiology of SARS-CoV-2.