Positive Selection of ORF1ab, ORF3a, and ORF8 Genes Drives the Early Evolutionary Trends of SARS-CoV-2 During the 2020 COVID-19 Pandemic

Velazquez‐Salinas, Lauro; Zárate, Selene; Eberl, Samantha; Gladue, Douglas P.; Novella, Isabel S.; Borca, Manuel V.

doi:10.3389/fmicb.2020.550674

Cited by 114 publications

(108 citation statements)

References 60 publications

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“…example, artefactual biases in mutational processes could confound signatures of mutational hotspots [29][30][31][32][33][34]. The issue of whether or not recombination has occurred during the outbreak is critical to the immunological battles against the virus and is under intense debate [7,[35][36][37][38][39][40][41]. Because many tests of recombination assume that all mutations can only occur once at each site, recurrent mutation and systematic errors can confound signatures of recombination [7,27,36].…”

Section: Plos Geneticsmentioning

confidence: 99%

Stability of SARS-CoV-2 phylogenies

et al. 2020

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The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral samples and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab—or protocol—specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein-coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation or recombination among viral lineages. We suggest how samples can be screened and problematic variants removed, and we plan to regularly inform the scientific community with our updated results as more SARS-CoV-2 genome sequences are shared (https://virological.org/t/issues-with-sars-cov-2-sequencing-data/473 and https://virological.org/t/masking-strategies-for-sars-cov-2-alignments/480). We also develop tools for comparing and visualizing differences among very large phylogenies and we show that consistent clade- and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.

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Section: Plos Geneticsmentioning

confidence: 99%

Stability of SARS-CoV-2 phylogenies

et al. 2020

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“…Of note, for the first time, Velazquez-Salinas et al identified the potential relevance of amino acid Y5865C in ORF1ab, showing that this residue is experimenting directional selection. Also, the increased evolutionary rate of ORF10 was identified by Velazquez-Salinas et al ( Velazquez-Salinas et al, 2020 ). Moreover, the exoribonuclease (ExoN) of NSP14 knockout mutant assays showed the replication roles of enzymatic activity in MERS-CoV and SARS-CoV-2 ( Ogando et al, 2020 ).…”

Section: Introductionmentioning

confidence: 78%

“…Using the genomic diversity of mutations in early SARS-CoV-2 strains, scientists have identified two distinct mutations, i.e., S or L type, with the S type considered more aggressive and faster spreading (Tang et al, 2020). From the analysis of early trends in the COVID-19 evolutionary patterns, Velazquez-Salinas et al for the first time identified the effect of mutation ORF1ab:5865 as a factor of phylogenetic divergence of SARS-CoV-2 ( Velazquez-Salinas et al, 2020 ). Our analysis of genetic variation in early SARS-CoV-2 strains found that most variations were in ORF1ab, and most variations in ORF1ab were nonsynonymous.…”

Section: Discussionmentioning

confidence: 99%

“…It was reported that more than 1000 lineages were being established before the national lockdown in the United Kingdom ( du Plessis et al, 2021 ). At the phylogeny of SARS-CoV-2, strains were identified as lineage A, B, and C according to variants, and the variant carrying the Y5865C mutation was associated with the lineage S or 19 B ( Velazquez-Salinas et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Molecular epidemiology analysis of early variants of SARS-CoV-2 reveals the potential impact of mutations P504L and Y541C (NSP13) in the clinical COVID-19 outcomes

Cao

Tian

et al. 2021

Infection, Genetics and Evolution

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Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global pandemic with alarming speed, comprehensively analyzing the mutation and evolution of early SARS-CoV-2 strains contributes to detect and prevent such virus. Here, we explored 1962 high-quality genomes of early SARS-CoV-2 strains obtained from 42 countries before April 2020. The changing trends of genetic variations in SARS-CoV-2 strains over time and country were subsequently identified. In addition, viral genotype mapping and phylogenetic analysis were performed to identify the variation features of SARS-CoV-2. Results showed that 57.89% of genetic variations involved in ORF1ab, most of which (68.85%) were nonsynonymous. Haplotype maps and phylogenetic tree analysis showed that amino acid variations in ORF1ab (p.5828P > L and p.5865Y > C, also NSP13: P504L and NSP13: Y541C) were the important characteristics of such clade. Furthermore, these variants showed more significant aggregation in the United States ( P = 2.92E-66, 95%) than in Australia or Canada, especially in strains from Washington State ( P = 1.56E-23, 77.65%). Further analysis demonstrated that the report date of the variants was associated with the date of increased infections and the date of recovery and fatality rate change in the United States. More importantly, the fatality rate in Washington State was higher (4.13%) and showed poorer outcomes ( P = 4.12E-21 in fatality rate, P = 3.64E-29 in death and recovered cases) than found in other states containing a small proportion of strains with such variants. Using sequence alignment, we found that variations at the 504 and 541 sites had functional effects on NSP13. In this study, we comprehensively analyzed genetic variations in SARS-CoV-2, gaining insights into amino acid variations in ORF1ab and COVID-19 outcomes.

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“…Over 198 sites on the viral genome containing recurrent mutations and 80 viral lineages were identified by May 5,6 . Sites on the SARS-CoV-2 genome are still undergoing positive selection 7,8 . Variants of the D614G and N501Y strains (both located on the S gene) have generated global concern for increased transmissibility with little evidence of association with disease severity [9][10][11][12][13][14] .…”

Section: Introductionmentioning

confidence: 99%

Increased SAR-CoV-2 shedding associated with reduced disease severity despite continually emerging genetic variants

Tang

Wang

Gao

et al. 2021

Preprint

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Since the first report of SARS-CoV-2 in December 2019, genetic variants have continued to emerge, complicating strategies for mitigating the disease burden of COVID-19. In this study, we investigated the emergence and spread of SARS-CoV-2 genetic variants in Missouri, examined viral shedding over time, and analyzed the associations among emerging genetic variants, viral shedding, and disease severity. The study population included COVID-19 positive patients from CoxHealth (Springfield, Missouri) and University of Missouri Health Care (UMHC; Columbia, Missouri) between March and October 2020. All positive SARS-CoV-2 nasopharyngeal swabs (n=8,735) from March-October 2020 were collected. Available viral genomes (n=184) from March to July were sequenced. Hospitalization status and length of stay were extracted from medical charts of 1,335 patients (UMHC and sequenced patients). The primary outcome was hospitalization status (yes or no) and length of hospital stay (days). For the 1,335 individuals, 44 were hospitalized and four died due to COVID-19. The average age was 34.35 (SD=16.82), with 55.1% females (n=735) and 44.7% males (n=596). Multiple introductions of SARS-CoV-2 into Missouri, primarily from Australia, Europe, and domestic states, were observed. Four local lineages rapidly emerged and spread across urban and rural regions in Missouri. While most Missouri viruses harbored Spike-D614G mutations, many unreported mutations were identified among Missouri viruses, including seven in the RNA-dependent RNA polymerase complex and Spike protein that were positively selected. A 15.6-fold increase in viral RNA levels in swab samples occurred from March to May and remained elevated through October. Accounting for comorbidities, individuals test-positive for COVID-19 with high viral loads were less likely to be hospitalized (odds ratio=0.39, 95% confidence interval=0.20, 0.77) and more likely to be discharged from the hospital sooner (hazard ratio=2.9, p=0.03) than those with low viral loads. Overall, the first eight months of the pandemic in Missouri saw multiple locally acquired mutants emerge and dominate in urban and rural locations. Although we were unable to find associations between specific variants and greater disease severity, Missouri COVID-positive individuals that presented with increased viral shedding had less severe disease by several measures.

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Positive Selection of ORF1ab, ORF3a, and ORF8 Genes Drives the Early Evolutionary Trends of SARS-CoV-2 During the 2020 COVID-19 Pandemic

Cited by 114 publications

References 60 publications

Stability of SARS-CoV-2 phylogenies

Stability of SARS-CoV-2 phylogenies

Molecular epidemiology analysis of early variants of SARS-CoV-2 reveals the potential impact of mutations P504L and Y541C (NSP13) in the clinical COVID-19 outcomes

Increased SAR-CoV-2 shedding associated with reduced disease severity despite continually emerging genetic variants

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