Human SARS-CoV-2 has evolved to increase U content and reduce genome size.

Infections caused by SARS-CoV-2 have brought great harm to human health. After transmission for over two years, SARS-CoV-2 has diverged greatly and formed dozens of different lineages. Understanding the trend of its genome evolution could help foresee difficulties in controlling transmission of the virus. In this study, we conducted an extensive monthly survey and in-depth analysis on variations of nucleotide, amino acid and codon numbers in 311,260 virus samples collected till January 2022. The results demonstrate that the evolution of SARS-CoV-2 is toward increasing U-content and reducing genome-size. C, G and A to U mutations have all contributed to this U-content increase. Mutations of C, G and A at codon position 1, 2 or 3 have no significant difference in most SARS-CoV-2 lineages. Current viruses are more cryptic and more efficient in replication, and are thus less virulent yet more infectious. Delta and Omicron variants have high mutability over other lineages, bringing new threat to human health. This trend of genome evolution may provide a clue for tracing the origin of SARS-CoV-2, because ancestral viruses should have lower U-content and probably bigger genome-size.

MicroRNAs for Virus Pathogenicity and Host Responses, Identified in SARS-CoV-2 Genomes, May Play Roles in Viral-Host Co-Evolution in Putative Zoonotic Host Species.

Our recent study identified seven key microRNAs (miR-8066, 5197, 3611, 3934-3p, 1307-3p, 3691-3p, 1468-5p) similar between SARS-CoV-2 and the human genome, pointing at miR-related mechanisms in viral entry and the regulatory effects on host immunity. To identify the putative roles of these miRs in zoonosis, we assessed their conservation, compared with humans, in some key wild and domestic animal carriers of zoonotic viruses, including bat, pangolin, pig, cow, rat, and chicken. Out of the seven miRs under study, miR-3611 was the most strongly conserved across all species; miR-5197 was the most conserved in pangolin, pig, cow, bat, and rat; miR-1307 was most strongly conserved in pangolin, pig, cow, bat, and human; miR-3691-3p in pangolin, cow, and human; miR-3934-3p in pig and cow, followed by pangolin and bat; miR-1468 was most conserved in pangolin, pig, and bat; while miR-8066 was most conserved in pangolin and pig. In humans, miR-3611 and miR-1307 were most conserved, while miR-8066, miR-5197, miR-3334-3p and miR-1468 were least conserved, compared with pangolin, pig, cow, and bat. Furthermore, we identified that changes in the miR-5197 nucleotides between pangolin and human can generate three new miRs, with differing tissue distribution in the brain, lung, intestines, lymph nodes, and muscle, and with different downstream regulatory effects on KEGG pathways. This may be of considerable importance as miR-5197 is localized in the spike protein transcript area of the SARS-CoV-2 genome. Our findings may indicate roles for these miRs in viral-host co-evolution in zoonotic hosts, particularly highlighting pangolin, bat, cow, and pig as putative zoonotic carriers, while highlighting the miRs' roles in KEGG pathways linked to viral pathogenicity and host responses in humans. This in silico study paves the way for investigations into the roles of miRs in zoonotic disease.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Mouse Genome Database (MGD): Knowledgebase for mouse-human comparative biology.

The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the community model organism knowledgebase for the laboratory mouse, a widely used animal model for comparative studies of the genetic and genomic basis for human health and disease. MGD is the authoritative source for biological reference data related to mouse genes, gene functions, phenotypes and mouse models of human disease. MGD is the primary source for official gene, allele, and mouse strain nomenclature based on the guidelines set by the International Committee on Standardized Nomenclature for Mice. MGD's biocuration scientists curate information from the biomedical literature and from large and small datasets contributed directly by investigators. In this report we describe significant enhancements to the content and interfaces at MGD, including (i) improvements in the Multi Genome Viewer for exploring the genomes of multiple mouse strains, (ii) inclusion of many more mouse strains and new mouse strain pages with extended query options and (iii) integration of extensive data about mouse strain variants. We also describe improvements to the efficiency of literature curation processes and the implementation of an information portal focused on mouse models and genes for the study of COVID-19.

The UCSC Genome Browser database: 2021 update.

For more than two decades, the UCSC Genome Browser database (https://genome.ucsc.edu) has provided high-quality genomics data visualization and genome annotations to the research community. As the field of genomics grows and more data become available, new modes of display are required to accommodate new technologies. New features released this past year include a Hi-C heatmap display, a phased family trio display for VCF files, and various track visualization improvements. Striving to keep data up-to-date, new updates to gene annotations include GENCODE Genes, NCBI RefSeq Genes, and Ensembl Genes. New data tracks added for human and mouse genomes include the ENCODE registry of candidate cis-regulatory elements, promoters from the Eukaryotic Promoter Database, and NCBI RefSeq Select and Matched Annotation from NCBI and EMBL-EBI (MANE). Within weeks of learning about the outbreak of coronavirus, UCSC released a genome browser, with detailed annotation tracks, for the SARS-CoV-2 RNA reference assembly.

OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more.

OMA is an established resource to elucidate evolutionary relationships among genes from currently 2326 genomes covering all domains of life. OMA provides pairwise and groupwise orthologs, functional annotations, local and global gene order conservation (synteny) information, among many other functions. This update paper describes the reorganisation of the database into gene-, group- and genome-centric pages. Other new and improved features are detailed, such as reporting of the evolutionarily best conserved isoforms of alternatively spliced genes, the inferred local order of ancestral genes, phylogenetic profiling, better cross-references, fast genome mapping, semantic data sharing via RDF, as well as a special coronavirus OMA with 119 viruses from the Nidovirales order, including SARS-CoV-2, the agent of the COVID-19 pandemic. We conclude with improvements to the documentation of the resource through primers, tutorials and short videos. OMA is accessible at https://omabrowser.org.

Hyperbolic rules of the cooperative organization of eukaryotic and prokaryotic genomes.

The author's method of oligomer sums for analysis of oligomer compositions of eukaryotic and prokaryotic genomes is described. The use of this method revealed the existence of general rules for the cooperative oligomeric organization of a wide list of genomes. These rules are called hyperbolic because they are associated with hyperbolic sequences including the harmonic progression 1, 1/2, 1/3, .., 1/n. These rules are demonstrated by examples of quantitative analysis of many genomes from the human genome to the genomes of archaea and bacteria. The hyperbolic (harmonic) rules, speaking about the existence of algebraic invariants in full genomic sequences, are considered as candidates for the role of universal rules for the cooperative organization of genomes. The results concerns additionally the problem of the origin of life. The described phenomenological results were obtained as consequences of the previously published author's quantum-information model of long DNA sequences. The oligomer sums method was also applied to the analysis of long genes and viruses including the COVID-19 virus; this revealed, in characteristics of many of them, the phenomenon of such rhythmically repeating deviations from model hyperbolic sequences, which are associated with DNA triplets. In addition, an application of the oligomer sums method is shown to the analysis of amino acid sequences in long proteins like the protein Titin. The topics of the algebraic harmony in living bodies and of the quantum-information approach in biology are discussed.

Using the spike protein feature to predict infection risk and monitor the evolutionary dynamic of coronavirus.

BACKGROUND: Coronavirus can cross the species barrier and infect humans with a severe respiratory syndrome. SARS-CoV-2 with potential origin of bat is still circulating in China. In this study, a prediction model is proposed to evaluate the infection risk of non-human-origin coronavirus for early warning. METHODS: The spike protein sequences of 2666 coronaviruses were collected from 2019 Novel Coronavirus Resource (2019nCoVR) Database of China National Genomics Data Center on Jan 29, 2020. A total of 507 human-origin viruses were regarded as positive samples, whereas 2159 non-human-origin viruses were regarded as negative. To capture the key information of the spike protein, three feature encoding algorithms (amino acid composition, AAC; parallel correlation-based pseudo-amino-acid composition, PC-PseAAC and G-gap dipeptide composition, GGAP) were used to train 41 random forest models. The optimal feature with the best performance was identified by the multidimensional scaling method, which was used to explore the pattern of human coronavirus. RESULTS: The 10-fold cross-validation results showed that well performance was achieved with the use of the GGAP (g = 3) feature. The predictive model achieved the maximum ACC of 98.18% coupled with the Matthews correlation coefficient (MCC) of 0.9638. Seven clusters for human coronaviruses (229E, NL63, OC43, HKU1, MERS-CoV, SARS-CoV, and SARS-CoV-2) were found. The cluster for SARS-CoV-2 was very close to that for SARS-CoV, which suggests that both of viruses have the same human receptor (angiotensin converting enzyme II). The big gap in the distance curve suggests that the origin of SARS-CoV-2 is not clear and further surveillance in the field should be made continuously. The smooth distance curve for SARS-CoV suggests that its close relatives still exist in nature and public health is challenged as usual. CONCLUSIONS: The optimal feature (GGAP, g = 3) performed well in terms of predicting infection risk and could be used to explore the evolutionary dynamic in a simple, fast and large-scale manner. The study may be beneficial for the surveillance of the genome mutation of coronavirus in the field.