A Computer Simulation of SARS-CoV-2 Mutation Spectra for Empirical Data Characterization and Analysis.

It is very important to compute the mutation spectra, and simulate the intra-host mutation processes by sequencing data, which is not only for the understanding of SARS-CoV-2 genetic mechanism, but also for epidemic prediction, vaccine, and drug design. However, the current intra-host mutation analysis algorithms are not only inaccurate, but also the simulation methods are unable to quickly and precisely predict new SARS-CoV-2 variants generated from the accumulation of mutations. Therefore, this study proposes a novel accurate strand-specific SARS-CoV-2 intra-host mutation spectra computation method, develops an efficient and fast SARS-CoV-2 intra-host mutation simulation method based on mutation spectra, and establishes an online analysis and visualization platform. Our main results include: (1) There is a significant variability in the SARS-CoV-2 intra-host mutation spectra across different lineages, with the major mutations from G- > A, G- > C, G- > U on the positive-sense strand and C- > U, C- > G, C- > A on the negative-sense strand; (2) our mutation simulation reveals the simulation sequence starts to deviate from the base content percentage of Alpha-CoV/Delta-CoV after approximately 620 mutation steps; (3) 2019-NCSS provides an easy-to-use and visualized online platform for SARS-Cov-2 online analysis and mutation simulation.

2019nCoVAS: Developing the Web Service for Epidemic Transmission Prediction, Genome Analysis, and Psychological Stress Assessment for 2019-nCoV.

Since the COVID-19 epidemic is still expanding around the world and poses a serious threat to human life and health, it is necessary for us to carry out epidemic transmission prediction, whole genome sequence analysis, and public psychological stress assessment for 2019-nCoV. However, transmission prediction models are insufficiently accurate and genome sequence characteristics are not clear, and it is difficult to dynamically assess the public psychological stress state under the 2019-nCoV epidemic. Therefore, this study develops a 2019nCoVAS web service (http://www.combio-lezhang.online/2019ncov/home.html) that not only offers online epidemic transmission prediction and lineage-associated underrepresented permutation (LAUP) analysis services to investigate the spreading trends and genome sequence characteristics, but also provides psychological stress assessments based on such an emotional dictionary that we built for 2019-nCoV. Finally, we discuss the shortcomings and further study of the 2019nCoVAS web service.