Browsing by Author "Shen, Jikui"

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    Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2
    (Frontiers Media, 2022-04-11) Li, Kailing; Wang, Audrey K.Y.; Liu, Sheng; Fang, Shuyi; Lu, Alex Z.; Shen, Jikui; Yang, Lei; Hu, Chang-Deng; Yang, Kai; Wan, Jun; BioHealth Informatics, School of Informatics and Computing
    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.
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    Enrichment of G‐to‐U Substitution in SARS‐CoV‐2 Functional Regions and Its Compensation via Concurrent Mutations
    (Wiley, 2025) Sulaiman, Xierzhatijiang; Han, Yan; Liu, Sheng; Li, Kailing; Shang, Marissa; Yang, Lei; White, Kenneth; Zang, Yong; Shen, Jikui; Wan, Jun; Medical and Molecular Genetics, School of Medicine
    We surveyed single nucleotide variant (SNV) patterns from 5 903 647 complete SARS-CoV-2 genomes. Among 10 012 SNVs, APOBEC-mediated C-to-U (C > U) deamination was the most prevalent, followed by G > U and other RNA editing-related substitutions including (A > G, U > C, G > A). However, C > U mutations were less frequent in functional regions, for example, S protein, intrinsic disordered regions, and nonsynonymous mutations, where G > U were over-represented. Notably, G-loss substitutions rarely appeared together. Instead, G-gain mutations tended to more frequently co-occur with others, with a marked preference in the S protein, suggesting a compensatory mechanism for G loss in G > U mutations. The temporal patterns revealed C > U frequency declined until late 2021 then resurged in early 2022. Conversely, G > U steadily decreased, with a pronounced drop in January 2022, coinciding with reduced COVID-19 severity. Vaccinated individuals exhibited a slightly but significantly higher C > U frequency and a notably lower G > U frequency compared to the unvaccinated group. Additionally, cancer patients had higher G > U frequency than general patients during the same period. Interestingly, none of the C > U SNVs were uniquely identified in 2724 environmental samples. These findings suggest novel functional roles of G > U in COVID-19 symptoms, potentially linked to oxidative stress and reactive oxygen species, while C > U remains the dominant substitution, likely driven by host immune-mediated RNA editing.
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    Genetic Spectrum and Distinct Evolution Patterns of SARS-CoV-2
    (Frontiers Media, 2020-09-25) Liu, Sheng; Shen, Jikui; Fang, Shuyi; Li, Kailing; Liu, Juli; Yang, Lei; Hu, Chang-Deng; Wan, Jun; Medical and Molecular Genetics, School of Medicine
    Four signature groups of frequently occurred single-nucleotide variants (SNVs) were identified in over twenty-eight thousand high-quality and high-coverage SARS-CoV-2 complete genome sequences, representing different viral strains. Some SNVs predominated but were mutually exclusively presented in patients from different countries and areas. These major SNV signatures exhibited distinguishable evolution patterns over time. A few hundred patients were detected with multiple viral strain-representing mutations simultaneously, which may stand for possible co-infection or potential homogenous recombination of SARS-CoV-2 in environment or within the viral host. Interestingly nucleotide substitutions among SARS-CoV-2 genomes tended to switch between bat RaTG13 coronavirus sequence and Wuhan-Hu-1 genome, indicating the higher genetic instability or tolerance of mutations on those sites or suggesting that major viral strains might exist between Wuhan-Hu-1 and RaTG13 coronavirus.
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    GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences
    (Oxford University Press, 2020-10-12) Fang, Shuyi; Li, Kailing; Shen, Jikui; Liu, Sheng; Liu, Juli; Yang, Lei; Hu, Chang-Deng; Wan, Jun; BioHealth Informatics, School of Informatics and Computing
    The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs.
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    Updated SARS-CoV-2 Single Nucleotide Variants and Mortality Association
    (Cold Spring Harbor Laboratory Press, 2021) Fang, Shuyi; Liu, Sheng; Shen, Jikui; Lu, Alex Z.; Zhang, Yucheng; Li, Kailing; Liu, Juli; Yang, Lei; Hu, Chang-Deng; Wan, Jun; BioHealth Informatics, School of Informatics and Computing
    Since its outbreak in December 2019, COVID-19 has caused 100,5844,555 cases and 2,167,313 deaths as of Jan 27, 2021. Comparing our previous study of SARS-CoV-2 single nucleotide variants (SNVs) before June 2020, we found out that the SNV clustering had changed considerably since June 2020. Apart from that the group SNVs represented by two non-synonymous mutations A23403G (S: D614G) and C14408T (ORF1ab: P4715L) became dominant and carried by over 95% genomes, a few emerging groups of SNVs were recognized with sharply increased monthly occurrence ratios up to 70% in November 2020. Further investigation revealed that several SNVs were strongly associated with the mortality, but they presented distinct distribution in specific countries, e.g., Brazil, USA, Saudi Arabia, India, and Italy. SNVs including G25088T, T25A, G29861T and G29864A were adopted in a regularized logistic regression model to predict the mortality status in Brazil with the AUC of 0.84. Protein structure analysis showed that the emerging subgroups of non-synonymous SNVs and those mortality-related ones in Brazil were located on protein surface area. The clashes in protein structure introduced by these mutations might in turn affect virus pathogenesis through conformation changes, leading to the difference in transmission and virulence. Particularly, we found that SNVs tended to occur in intrinsic disordered regions (IDRs) of Spike (S) and ORF1ab, suggesting a critical role of SNVs in protein IDRs to determine protein folding and immune evasion.