Intra-host mutation rate of acute SARS-CoV-2 infection during the initial pandemic wave.

SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations. Viral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) ≥ 0.25, ≥ 0.5 and ≥ 0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with (ΔNSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity. Forty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI 90.8-96.4], 40.7 (95%CI 38.9-42.6) and 34.7 (95%CI 33.0-36.4) substitutions/genome/year at AF ≥ 0.25, ≥ 0.5, ≥ 0.75 respectively. Mutation rate in ΔNSP-14 were significantly elevated at AF ≥ 0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies. Intra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.

CriSNPr, a single interface for the curated and de novo design of gRNAs for CRISPR diagnostics using diverse Cas systems.

CRISPR-based diagnostics (CRISPRDx) have improved clinical decision-making, especially during the COVID-19 pandemic, by detecting nucleic acids and identifying variants. This has been accelerated by the discovery of new and engineered CRISPR effectors, which have expanded the portfolio of diagnostic applications to include a broad range of pathogenic and non-pathogenic conditions. However, each diagnostic CRISPR pipeline necessitates customized detection schemes based on the fundamental principles of the Cas protein used, its guide RNA (gRNA) design parameters, and the assay readout. This is especially relevant for variant detection, a low-cost alternative to sequencing-based approaches for which no in silico pipeline for the ready-to-use design of CRISPRDx currently exists. In this manuscript, we fill this lacuna using a unified web server, CriSNPr (CRISPR-based SNP recognition), which provides the user with the opportunity to de novo design gRNAs based on six CRISPRDx proteins of choice (Fn/enFnCas9, LwCas13a, LbCas12a, AaCas12b, and Cas14a) and query for ready-to-use oligonucleotide sequences for validation on relevant samples. Furthermore, we provide a database of curated pre-designed gRNAs as well as target/off-target for all human and SARS-CoV-2 variants reported thus far. CriSNPr has been validated on multiple Cas proteins, demonstrating its broad and immediate applicability across multiple detection platforms. CriSNPr can be found at http://crisnpr.igib.res.in/.

A common variant close to the "tripwire" linker region of NLRP1 contributes to severe COVID-19.

OBJECTIVE AND DESIGN: The heterogeneity of response to SARS-CoV-2 infection is directly linked to the individual genetic background. Genetic variants of inflammasome-related genes have been pointed as risk factors for several inflammatory sterile and infectious disease. In the group of inflammasome receptors, NLRP1 stands out as a good novel candidate as severity factor for COVID-19 disease. METHODS: To address this question, we performed an association study of NLRP1, DPP9, CARD8, IL1B, and IL18 single nucleotide variants (SNVs) in a cohort of 945 COVID-19 patients. RESULTS: The NLRP1 p.Leu155His in the linker region, target of viral protease, was significantly associated to COVID-19 severity, which could contribute to the excessive cytokine release reported in severe cases. CONCLUSION: Inflammasome genetic background contributes to individual response to SARS-CoV-2.

Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2.

The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2 (GESS v2 https://shiny.ph.iu.edu/GESS_v2/) is an updated version of GESS, which has offered a handy query platform to analyze single-nucleotide variants (SNVs) on millions of high coverages and high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete genomes provided by the Global Initiative on Sharing Avian Influenza Data (GISAID). Including the tools in the first version, the GESS v2 is embedded with new functions, which allow users to search SNVs, given the viral nucleotide or amino acid sequence. The GESS v2 helps users to identify SNVs or SARS-CoV-2 lineages enriched in countries of user's interest and show the migration path of a selected lineage on a world map during specific time periods chosen by the users. In addition, the GESS v2 can recognize the dynamic variations of newly emerging SNVs in each month to help users monitor SNVs, which will potentially become dominant soon. More importantly, multiple sets of analyzed results about SNVs can be downloaded directly from the GESS v2 by which users can conduct their own independent research. With these significant updates, the GESS v2 will continue to serve as a public open platform for researchers to explore SARS-CoV-2 evolutionary patterns from the perspectives of the prevalence and impact of SNVs.

Genomic chronicle of SARS-CoV-2: a mutational analysis with over 1 million genome sequences.

Use of information technologies to analyse big data on SARS-CoV-2 genome provides an insight for tracking variations and examining the evolution of the virus. Nevertheless, storing, processing, alignment and analyses of these numerous genomes are still a challenge. In this study, over 1 million SARS-CoV-2 genomes have been analysed to show distribution and relationship of variations that could enlighten development and evolution of the virus. In all genomes analysed in this study, a total of over 215M SNVs have been detected and average number of SNV per isolate was found to be 21.83. Single nucleotide variant (SNV) average is observed to reach 31.25 just in March 2021. The average variation number of isolates is increasing and compromising with total case numbers around the world. Remarkably, cytosine deamination, which is one of the most important biochemical processes in the evolutionary development of coronaviruses, accounts for 46% of all SNVs seen in SARS-CoV-2 genomes within 16 months. This study is one of the most comprehensive SARS-CoV-2 genomic analysis study in terms of number of genomes analysed in an academic publication so far, and reported results could be useful in monitoring the development of SARS-CoV-2.

Genetic Control of Human Infection with SARS-CoV-2.

In 2019, the SARS-CoV-2 beta-coronavirus, which caused a pandemic of severe acute respiratory viral infection COVID-19 (from COronaVIrus Disease 2019), was first detected. The susceptibility to SARS-CoV-2 and the nature of the course of the COVID-19 clinical picture are determined by many factors, including genetic characteristics of both the pathogen and the human. The SARS-CoV-2 genome has a similarity to the genomes of other coronaviruses, which are pathogenic for humans and cause a severe course of infection: 79% to the SARS-CoV genome and 50% to the MERS-CoV genome. The most significant differences between SARS-CoV-2 and other coronaviruses are recorded in the structure of the gene of the S protein, a key protein responsible for the virus binding to the receptor of the host organism cells. In particular, substitutions in the S protein of SARS-CoV-2, leading to the formation of the furin cleavage site that is absent in other SARS-like coronaviruses, were identified, which may explain the high pathogenicity of SARS-CoV-2. In humans, the genes that are significant for the initial stages of infection include ACE2, ANPEP, DPP4 (encode receptors for coronavirus binding); TMPRSS2, FURIN, TMPRSS11D, CTSL, CTSB (encode proteases involved in the entry of the coronavirus into the cell); DDX1 (the gene of ATP-dependent RNA helicase DDX1, which promotes replication of coronaviruses); and IFITM1, IFITM2, and IFITM3 (encode interferon-induced transmembrane proteins with an antiviral effect). These genes are expressed in many tissues (including those susceptible to the effects of SARS-CoV-2); rare and frequent variants that affect the structure of the encoded protein and its properties and expression level are described in them. A number of common genetic variants with proven functional significance are characterized by the variability in the allele frequency in the world's populations, which can determine interpopulation differences in the prevalence of COVID-19 and in the clinical features of the course of this pathology. The expression level of genes that are important for the formation of the susceptibility to SARS-CoV-2 is affected by epigenetic modifications, comorbidities at the time of infection, taking medications, and bad habits.

Genetics Insight for COVID-19 Susceptibility and Severity: A Review.

Coronavirus disease (COVID-19) presents a broad spectrum of clinical manifestations ranging from an asymptomatic to a severe clinical course. The host genetic background influence on the susceptibility and outcome of multiples infectious diseases has been previously reported. Herein, we aimed to describe relevant identified genetic variants and those potentially related to the inter-individual variability of COVID-19 susceptibility and/or severity considering the physiopathological pathway of the disease The HLA-A*25:01, -B*15:27, -B*46:01, -C*01:02, and -C*07:29 alleles have been associated with COVID-19 susceptibility; while HLA-A*02:02, -B*15:03, and -C*12:03 have been identified as low-risk alleles. Variants in cytokine genes such as IL1B, IL1R1, IL1RN, IL6, IL17A, FCGR2A, and TNF could be related to disease susceptibility and cytokine storm, and/or COVID-19 complications (e.g., venous thrombosis). Several variants in ACE2 and TMPRSS2 affecting the expression of the receptors related to COVID-19 have been associated with the disease susceptibility and risk factors. Finally, two GWAS have identified the loci 3p21.31 (LZTFL1, SLC6A20, CCR9, FYCO1, CXCR6, and XCR1) and 9q34.2 (ABO) with COVID-19 severity. Heterogeneous results in the association of genetic variants with COVID-19 susceptibility and severity were observed. The mechanism of identified risk-genes and studies in different populations are still warranted.

Rapid and accurate nucleobase detection using FnCas9 and its application in COVID-19 diagnosis.

Rapid detection of DNA/RNA pathogenic sequences or variants through point-of-care diagnostics is valuable for accelerated clinical prognosis, as witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are tough to implement with limited resources, necessitating the development of accurate and robust alternative strategies. Here, we report FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that utilizes a direct Cas9 based enzymatic readout for detecting nucleobase and nucleotide sequences without trans-cleavage of reporter molecules. We also demonstrate that FELUDA is 100% accurate in detecting single nucleotide variants (SNVs), including heterozygous carriers, and present a simple web-tool JATAYU to aid end-users. FELUDA is semi-quantitative, can adapt to multiple signal detection platforms, and deploy for versatile applications such as molecular diagnosis during infectious disease outbreaks like COVID-19. Employing a lateral flow readout, FELUDA shows 100% sensitivity and 97% specificity across all ranges of viral loads in clinical samples within 1hr. In combination with RT-RPA and a smartphone application True Outcome Predicted via Strip Evaluation (TOPSE), we present a prototype for FELUDA for CoV-2 detection closer to home.

Genomic characterization and phylogenetic analysis of the first SARS-CoV-2 variants introduced in Lebanon.

BACKGROUND: In December 2019, the COVID-19 pandemic initially erupted from a cluster of pneumonia cases of unknown origin in the city of Wuhan, China. Presently, it has almost reached 94 million cases worldwide. Lebanon on the brink of economic collapse and its healthcare system thrown into turmoil, has previously managed to cope with the initial SARS-CoV-2 wave. In this study, we sequenced 11 viral genomes from positive cases isolated between 2 February 2020 and 15 March 2020. METHODS: Sequencing data was quality controlled, consensus sequences generated, and a maximum-likelihood tree was generated with IQTREE v2. Genetic lineages were assigned with Pangolin v1.1.14 and single nucleotide variants (SNVs) were called from read files and manually curated from consensus sequence alignment through JalView v2.11 and the genomic mutational interference with molecular diagnostic tools was assessed with the CoV-GLUE pipeline. Phylogenetic analysis of whole genome sequences confirmed a multiple introduction scenario due to international travel. RESULTS: Three major lineages were identified to be circulating in Lebanon in the studied period. The B.1 (20A clade) was the most prominent, followed by the B.4 lineage (19A clade) and the B.1.1 lineage (20B clade). SNV analysis showed 15 novel mutations from which only one was observed in the spike region.

HOW GENETICISTS CONTRIBUTE TO UNDERSTANDING OF COVID-19 DISEASE PATHOGENICITY.

Human populations are faced to the COVID-19 pandemic due to the emerging SARS-CoV-2 coronavirus originating from Wuhan (China) and with dramatic Public Health consequences. Despite periods of panic, the scientific community demonstrated an incredible innovation potential and energy ending up in one year with new vaccines to be used in population. Researchers are interrogating on how individual genetic differences contribute to the diversity of clinical manifestations or ethnic and geographic disparities of COVID-19. While efforts were spent to understand mechanistically the infectious potential of the virus, recent progresses in molecular genetics and bioinformatics allowed the characterization of viral sequence and construction of phylogeographical maps of viral dispersion worldwide. These data will help understanding epidemiological disparities among continents and ethnic populations. Much effort was also spent in analyzing host genetics by studying individual genes involved in innate and immune responses or explaining pathogenesis of comorbidities that complicate the fate of elderly patients. Several international consortia launched already Genome wide Association Studies (GWAS) and whole genome sequencing strategies to identify genetic markers with immediate application in patients at risk of respiratory failure. These new genetic data are important not only for understanding susceptibility factors for COVID-19 but they also contain an important message of hope for mankind warranting our survival and health.

Structural Variability, Expression Profile, and Pharmacogenetic Properties of TMPRSS2 Gene as a Potential Target for COVID-19 Therapy.

The human serine protease serine 2 TMPRSS2 is involved in the priming of proteins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and represents a possible target for COVID-19 therapy. The TMPRSS2 gene may be co-expressed with SARS-CoV-2 cell receptor genes angiotensin-converting enzyme 2 (ACE2) and Basigin (BSG), but only TMPRSS2 demonstrates tissue-specific expression in alveolar cells according to single-cell RNA sequencing data. Our analysis of the structural variability of the TMPRSS2 gene based on genome-wide data from 76 human populations demonstrates that a functionally significant missense mutation in exon 6/7 in the TMPRSS2 gene is found in many human populations at relatively high frequencies, with region-specific distribution patterns. The frequency of the missense mutation encoded by rs12329760, which has previously been found to be associated with prostate cancer, ranged between 10% and 63% and was significantly higher in populations of Asian origin compared with European populations. In addition to single-nucleotide polymorphisms, two copy number variants were detected in the TMPRSS2 gene. A number of microRNAs have been predicted to regulate TMPRSS2 and BSG expression levels, but none of them is enriched in lung or respiratory tract cells. Several well-studied drugs can downregulate the expression of TMPRSS2 in human cells, including acetaminophen (paracetamol) and curcumin. Thus, the interactions of TMPRSS2 with SARS-CoV-2, together with its structural variability, gene-gene interactions, expression regulation profiles, and pharmacogenomic properties, characterize this gene as a potential target for COVID-19 therapy.