Coronavirus Genome Research Articles

Adaptive Evolution of the Fox Coronavirus Based on Genome-Wide Sequence Analysis.

Purpose To report the first complete fox coronavirus (CoV) genome sequence obtained through genome-wide amplifications and to understand the adaptive evolution of fox CoV. Methods Anal swab samples were collected from 35 foxes to detect the presence of CoV and obtain the virus sequence. Phylogenetic analysis was conducted using MrBayes. The possibility of recombination within these sequences was assessed using GARD. Analysis of the levels of selection pressure experienced by these sequences was assessed using methods on both the PAML and Data Monkey platforms. Results Of the 35 samples, two were positive, and complete genome sequences for the viruses were obtained. Phylogenetic analysis, using Bayesian methods, of these sequences, together with other CoV sequences, revealed that the fox CoV sequences clustered with canine coronavirus (CCoV) sequences, with sequences from other carnivores more distantly related. In contrast to the feline, ferret and mink CoV sequences that clustered into species-specific clades, the fox CoV fell within the CCoV clade. Minimal evidence for recombination was found among the sequences. A total of 7, 3, 14, and 2 positively selected sites were identified in the M, N, S, and 7B genes, respectively, with 99, 111, and 581 negatively selected sites identified in M, N, and S genes, respectively. Conclusion The complete genome sequence of fox CoV has been obtained for the first time. The results suggest that the genome sequence of fox CoV may have experienced adaptive evolution in the genes replication, entry, and virulence. The number of sites in each gene that experienced negative selection is far greater than the number that underwent positive selection, suggesting that most of the sequence is highly conserved and important for viral survive. However, positive selection at a few sites likely aided these viruses to adapt to new environments.

Profiling of the most reliable mutations from sequenced SARS-CoV-2 genomes scattered in Uzbekistan

Due to rapid mutations in the coronavirus genome over time and re-emergence of multiple novel variants of concerns (VOC), there is a continuous need for a periodic genome sequencing of SARS-CoV-2 genotypes of particular region. This is for on-time development of diagnostics, monitoring and therapeutic tools against virus in the global pandemics condition. Toward this goal, we have generated 18 high-quality whole-genome sequence data from 32 SARS-CoV-2 genotypes of PCR-positive COVID-19 patients, sampled from the Tashkent region of Uzbekistan. The nucleotide polymorphisms in the sequenced sample genomes were determined, including nonsynonymous (missense) and synonymous mutations in coding regions of coronavirus genome. Phylogenetic analysis grouped fourteen whole genome sample sequences (1, 2, 4, 5, 8, 10–15, 17, 32) into the G clade (or GR sub-clade) and four whole genome sample sequences (3, 6, 25, 27) into the S clade. A total of 128 mutations were identified, consisting of 45 shared and 83 unique mutations. Collectively, nucleotide changes represented one unique frameshift mutation, four upstream region mutations, six downstream region mutations, 50 synonymous mutations, and 67 missense mutations. The sequence data, presented herein, is the first coronavirus genomic sequence data from the Republic of Uzbekistan, which should contribute to enrich the global coronavirus sequence database, helping in future comparative studies. More importantly, the sequenced genomic data of coronavirus genotypes of this study should be useful for comparisons, diagnostics, monitoring, and therapeutics of COVID-19 disease in local and regional levels.

SHAPE-guided RNA structure homology search and motif discovery

The rapidly growing popularity of RNA structure probing methods is leading to increasingly large amounts of available RNA structure information. This demands the development of efficient tools for the identification of RNAs sharing regions of structural similarity by direct comparison of their reactivity profiles, hence enabling the discovery of conserved structural features. We here introduce SHAPEwarp, a largely sequence-agnostic SHAPE-guided algorithm for the identification of structurally-similar regions in RNA molecules. Analysis of Dengue, Zika and coronavirus genomes recapitulates known regulatory RNA structures and identifies novel highly-conserved structural elements. This work represents a preliminary step towards the model-free search and identification of shared and conserved RNA structural features within transcriptomes.

Coronavirus Genomes and Unique Mutations in Structural and Non-Structural Proteins in Pakistani SARS-CoV-2 Delta Variants during the Fourth Wave of the Pandemic

Genomic epidemiology of SARS-CoV-2 is imperative to explore the transmission, evolution, and also pathogenicity of viruses. The emergence of SARS-CoV-2 variants of concern posed a severe threat to the global public health efforts. To assess the potential consequence of these emerging variants on public health, continuous molecular epidemiology is of vital importance. The current study has been designed to investigate the major SARS-CoV-2 variants and emerging mutations in virus structural and non-structural proteins (NSP) during the fourth wave in September 2021 from the Punjab province of Pakistan. Twenty SARS-CoV-2 positive samples have been collected from major cities were subjected to next-generation sequencing. Among the 20 whole genomes (GenBank Accession SRR16294858-SRR16294877), 2 samples failed to be completely sequenced. These genome sequences harbored 207 non-synonymous mutations, among which 19 were unique to GISAID. The genome sequences were detected: Delta 21I, 21J variants (B.1.617.2). Mutation’s spike_F157del, spike_P681R, spike_T478K, spike_T19R, spike_L452R, spike_D614G, spike_G142D, spike_E156G, and spike_R158del have been detected in all samples where K1086Q, E554K, and C1250W were unique in spike protein. These genomic sequences also harbored 129 non-synonymous mutations in NSP. The most common were NSP3_P1469S (N = 17), NSP3_A488S (N = 17), NSP3_P1228L (N = 17), NSP4_V167L (N = 17), NSP4_T492I (N = 17), NSP6_T77A (N = 17), NSP14_A394V (N = 17), NSP12_G671S (N = 18), and NSP13_P77L (N = 18). The mutation, F313Y in NSP12, detected in the current study, was found in a single isolate from Belgium. Numerous other unique mutations have been detected in the virus papain-like protease (NSP3), main protease (NSP5), and RNA-dependent RNA polymerase (NSP12). The most common non-synonymous mutations in the spike protein were subjected to stability analysis, exhibiting a stabilizing effect on structures. The presence of Delta variants may affect therapeutic efforts and vaccine efficacy. Continuous genomic epidemiology of SARS-CoV-2 in Pakistan may be useful for better management of SARS-CoV-2 infections.

Evitar: designing anti-viral RNA therapies against future RNA viruses.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the threat of emerging respiratory viruses and has exposed the lack of availability of off-the-shelf therapeutics against new RNA viruses. Previous research has established the potential that siRNAs and RNA-targeting CRISPR have in combating known RNA viruses. However, the feasibility and tools for designing anti-viral RNA therapeutics against future RNA viruses have not yet been established. We develop the Emerging-Virus-Targeting RNA (Evitar) pipeline for designing anti-viral siRNAs and CRISPR Cas13a guide RNA (gRNA) sequences. Within Evitar, we develop Greedy Algorithm with Redundancy and Similarity-weighted Greedy Algorithm with Redundancy to enhance the performance. Time simulations using known coronavirus genomes deposited as early as 10 years prior to the COVID-19 outbreak show that at least three SARS-CoV-2-targeting siRNAs are among the top 30 pre-designed siRNAs. In addition, among the top 19 pre-designed gRNAs, there are three SARS-CoV-2-targeting Cas13a gRNAs that could be predicted using information from 2011. Before-the-outbreak design is also possible against the MERS-CoV virus and the 2009-H1N1 swine flu virus. Designed siRNAs are further shown to suppress SARS-CoV-2 viral sequences using in vitro reporter assays. Our results support the utility of Evitar to pre-design anti-viral siRNAs/gRNAs against future viruses. Therefore, we propose the development of a collection consisting of roughly 30 pre-designed, safety-tested and off-the-shelf siRNA/CRISPR therapeutics that could accelerate responses to future RNA virus outbreaks. Codes are available at GitHub (https://github.com/dingyaozhang/Evitar). Supplementary data are available at Bioinformatics online.

Coronavirus Genus Recognition Based on Prototype Virus Variants

Method named as variant approach to recognizing genus of coronavirus that is based on frequency of codon distribution in viral ORF1ab and genes of structural proteins (S, M and N) was proposed in the work. This method uses modified statistics whose efficiency was demonstrated earlier for flavivirus species recognition. To recognize genus of coronavirus the variant approach considers both various combinations of several structural coronavirus genes and individual structural genes. Finally, coronavirus genus is determined in the result of analysis of all variants considered. The method proposed was developed with the help of learning sample from prototype viral variants of Alphacoronavirus, Betacoronavirus, Deltacoronavirus and Gammacoronavirus genus. Application of the variant approach to recognizing genus of coronavirus has demonstrated the approach high assurance at level of 95 %. Among all variants of joint analysis, the most reliability (98 %) in recognizing genus has been achieved if codon frequency of the ORF1ab was used. Variant approach has revealed a phenomenon of mosaic structure in coronavirus genomes, i.e., when the results of genus recognition for a few genes differ from final conclusion about coronavirus genus. It seems that such phenomenon reflects homologous recombinations of the genes between various species of the coronaviruses and plasticity of their genomes in evolutionary processes.

Comparative analysis of alignment-free genome clustering and whole genome alignment-based phylogenomic relationship of coronaviruses.

The SARS-CoV-2 is the third coronavirus in addition to SARS-CoV and MERS-CoV that causes severe respiratory syndrome in humans. All of them likely crossed the interspecific barrier between animals and humans and are of zoonotic origin, respectively. The origin and evolution of viruses and their phylogenetic relationships are of great importance for study of their pathogenicity and development of antiviral drugs and vaccines. The main objective of the presented study was to compare two methods for identifying relationships between coronavirus genomes: phylogenetic one based on the whole genome alignment followed by molecular phylogenetic tree inference and alignment-free clustering of triplet frequencies, respectively, using 69 coronavirus genomes selected from two public databases. Both approaches resulted in well-resolved robust classifications. In general, the clusters identified by the first approach were in good agreement with the classes identified by the second using K-means and the elastic map method, but not always, which still needs to be explained. Both approaches demonstrated also a significant divergence of genomes on a taxonomic level, but there was less correspondence between genomes regarding the types of diseases they caused, which may be due to the individual characteristics of the host. This research showed that alignment-free methods are efficient in combination with alignment-based methods. They have a significant advantage in computational complexity and provide valuable additional alternative information on the genomes relationships.

Did the SARS-CoV-2 Come from Wild, Mutagenic or Artificial Type? Complete Genome Analysis

Questions that come to mind about the true genetic origin of the novel coronavirus and its direct source. As it is likely that these questions will be answered through aspects of the relationship between science and intelligence, the results of which will converge together in the end to some evidence. Materials and methods: The 29 complete coronavirus and HIV genomes were collected from various countries at random and conducted various bioinformatics instruments in order to find connections between viral sequences from various sources. Results: The closest similarity between the SARS-CoV-2 genomes approximately (99.98%). The small difference between genome sequences is considered as weak mutations occur even at the present time. This study revealed that the novel coronavirus had a structure identical to the HIV virus which it reached approximately 46.33%. Conclusions: It is not possible for the SARS-CoV-2 to be related to HIV through mutation, manipulation, or laboratory artificial. Laboratory mutation occurred in the Wuhan lab and led to the outbreak of the epidemic, deliberately or accidentally, and this will be determined later.

Correlated sequence signatures are present within the genomic 5'UTR RNA and NSP1 protein in coronaviruses.

The 5′UTR part of coronavirus genomes plays key roles in the viral replication cycle and translation of viral mRNAs. The first 75–80 nt, also called the leader sequence, are identical for genomic mRNA and subgenomic mRNAs. Recently, it was shown that cooperative actions of a 5′UTR segment and the nonstructural protein NSP1 are essential for both the inhibition of host mRNAs and for specific translation of viral mRNAs. Here, sequence analyses of both the 5′UTR RNA segment and the NSP1 protein have been done for several coronaviruses, with special attention to the betacoronaviruses. The conclusions are: (i) precise specific molecular signatures can be found in both the RNA and the NSP1 protein; (ii) both types of signatures correlate between each other. Indeed, definite sequence motifs in the RNA correlate with sequence motifs in the protein, indicating a coevolution between the 5′UTR and NSP1 in betacoronaviruses. Experimental mutational data on 5′UTR and NSP1 from SARS-CoV-2 using cell-free translation extracts support these conclusions and show that some conserved key residues in the amino-terminal half of the NSP1 protein are essential for evasion to the inhibitory effect of NSP1 on translation.

Mutations in the genome of severe acute respiratory syndrome coronavirus 2: implications for COVID-19 severity and progression.

Coronaviridae is a large family of enveloped, positive-strand RNA viruses that has plagued the world since it was discovered in humans in the 1960s. The recent severe acute respiratory syndrome coronavirus (SARS-CoV)-2 pandemic has already exceeded the number of combined cases and deaths witnessed during previous SARS-CoV and Middle East respiratory syndrome-CoV epidemics in the last two decades. This narrative review focuses on genomic mutations in SARS-CoV-2 and their impact on the severity and progression of COVID-19 in light of reported data in the literature. Notable SARS-CoV-2 mutations associated with open reading frames, the S glycoprotein, and nucleocapsid protein, currently circulating globally, are discussed along with emerging mutations such as those in the SARS-CoV-2 VUI 202012/01 variant in the UK and other European countries, the 484K.V2 and P.1 variants in Brazil, the B.1.617 variant in India, and South African variants 501Y.V2 and B.1.1.529 (omicron). These variants have the potential to influence the receptor binding domain, host–virus fusion, and SARS-CoV-2 replication. Correlating these mutations with disease dynamics could help us understand their pathogenicity and design appropriate therapeutics.

Unraveling the antiviral activity of plitidepsin against SARS-CoV-2 by subcellular and morphological analysis

The pandemic caused by the new coronavirus SARS-CoV-2 has made evident the need for broad-spectrum, efficient antiviral treatments to combat emerging and re-emerging viruses. Plitidepsin is an antitumor agent of marine origin that has also shown a potent pre-clinical efficacy against SARS-CoV-2. Plitidepsin targets the host protein eEF1A (eukaryotic translation elongation factor 1 alpha) and affects viral infection at an early, post-entry step. Because electron microscopy is a valuable tool to study virus-cell interactions and the mechanism of action of antiviral drugs, in this work we have used transmission electron microscopy (TEM) to evaluate the effects of plitidepsin in SARS-CoV-2 infection in cultured Vero E6 cells 24 and 48h post-infection. In the absence of plitidepsin, TEM morphological analysis showed double-membrane vesicles (DMVs), organelles that support coronavirus genome replication, single-membrane vesicles with viral particles, large vacuoles with groups of viruses and numerous extracellular virions attached to the plasma membrane. When treated with plitidepsin, no viral structures were found in SARS-CoV-2-infected Vero E6 cells. Immunogold detection of SARS-CoV-2 nucleocapsid (N) protein and double-stranded RNA (dsRNA) provided clear signals in cells infected in the absence of plitidepsin, but complete absence in cells infected and treated with plitidepsin. The present study shows that plitidepsin blocks the biogenesis of viral replication organelles and the morphogenesis of virus progeny. Electron microscopy morphological analysis coupled to immunogold labeling of SARS-CoV-2 products offers a unique approach to understand how antivirals such as plitidepsin work.

Population Genomics Approaches for Genetic Characterization of SARS-CoV-2 Lineages.

The genome of the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), has been sequenced at an unprecedented scale leading to a tremendous amount of viral genome sequencing data. To assist in tracing infection pathways and design preventive strategies, a deep understanding of the viral genetic diversity landscape is needed. We present here a set of genomic surveillance tools from population genetics which can be used to better understand the evolution of this virus in humans. To illustrate the utility of this toolbox, we detail an in depth analysis of the genetic diversity of SARS-CoV-2 in first year of the COVID-19 pandemic. We analyzed 329,854 high-quality consensus sequences published in the GISAID database during the pre-vaccination phase. We demonstrate that, compared to standard phylogenetic approaches, haplotype networks can be computed efficiently on much larger datasets. This approach enables real-time lineage identification, a clear description of the relationship between variants of concern, and efficient detection of recurrent mutations. Furthermore, time series change of Tajima's D by haplotype provides a powerful metric of lineage expansion. Finally, principal component analysis (PCA) highlights key steps in variant emergence and facilitates the visualization of genomic variation in the context of SARS-CoV-2 diversity. The computational framework presented here is simple to implement and insightful for real-time genomic surveillance of SARS-CoV-2 and could be applied to any pathogen that threatens the health of populations of humans and other organisms.

One-Step Assembly of a Porcine Epidemic Diarrhea Virus Infectious cDNA Clone by Homologous Recombination in Yeast: Rapid Manipulation of Viral Genome With CRISPR/Cas9 Gene-Editing Technology.

Porcine epidemic diarrhea virus (PEDV), a swine enteric coronavirus causing acute diarrhea in piglets, is one of the major threatens to the pork industry globally. Reverse genetics is a valuable tool for the virological study and vaccine development for coronaviruses. Due to the large size and unstable problem in Escherichia coli of coronavirus genome, construction and manipulation of reverse genetics system for coronaviruses remain laborious and time-consuming. In this study, a reverse genetics system of the genotype II PEDV strain HM was generated using the transformation-associated recombination (TAR) technology in yeast within 1 week. The rescued virus (rPEDV) exhibited similar growth properties to the wild-type virus in vitro. With this PEDV infectious cDNA clone, CRISPR/Cas9 technology and homologous recombination were combined to generate a recombinant virus rPEDV-EGFP in which the ORF3 gene was swapped with an EGFP gene. The reporter virus displayed similar growth properties to the parental virus rPEDV and remained stable during serial passage in vitro. Of note, the strategies of construction and manipulation of PEDV infectious cDNA clone are extremely simple and efficient, which could be applied for other RNA viruses and DNA viruses.

Ribosome Profiling: A Useful Approach to Discover Hidden Corners of SARS-CoV-2.

Following SARS-CoV-2 China epidemic in the December 2019, researches have attended to the genome of novel coronavirus. Hidden corners of SARS-CoV-2, maybe a shiny way to discover its pathogenicity and virulence. To design therapeutic agents, it is critical to map the complete repertoire of viral-translated proteins. Ribosome profiling is considered as a snapshot of all active ribosomes in a cell at a specific time point.

Detection of intra-family coronavirus genome sequences through graphical representation and artificial neural network

In this study, chaos game representation (CGR) is introduced for investigating the pattern of genome sequences. It is an image representation of the genome for the overall visualization of the sequence. The CGR representation is a mapping technique that assigns each sequence base into the respective position in the two-dimension plane to portray the DNA sequence. Importantly, CGR provides one to one mapping to nucleotides as well as sequence. A coordinate of the CGR plane can tell the corresponding base and its location in the original genome. Therefore, the whole nucleotide sequence (until the current nucleotide) can be restored from the one point of the CGR. In this study, CGR coupled with artificial neural network (ANN) is introduced as a new way to represent the genome and to classify intra-coronavirus sequences. A hierarchy clustering study is done to validate the approach and found to be more than 90% accurate while comparing the result with the phylogenetic tree of the corresponding genomes. Interestingly, the method makes the genome sequence significantly shorter (more than 99% compressed) saving the data space while preserving the genome features.

Evaluation of potential miRNA sponge effects of SARS genomes in human

To date the coronavirus family is composed of seven different viruses which were commonly known as cold viruses until the appearance of the severe acute respiratory coronavirus (SARS-CoV) in 2002, the middle east respiratory syndrome coronavirus (MERS) in 2012 and the severe acute respiratory coronavirus 2 (SARS-CoV-2) which caused the COVID-19 global pandemic in 2019. Using bioinformatic approaches we tested the potential interactions of human miRNAs, expressed in pulmonary epithelial cells, with the available coronavirus genomes. Putative miRNA binding sites were then compared between pathogenic and non pathogenic virus groups. The pathogenic group shares 6 miRNA binding sites that can be potentially involved in the sequestration of miRNAs already known to be associated with deep vein thrombosis. We then analysed ∼100k SARS-CoV-2 variant genomes for their potential interaction with human miRNAs and this study highlighted a group of 97 miRNA binding sites which is present in all the analysed genomes. Among these, we identified 6 miRNA binding sites specific for SARS-CoV-2 and the other two pathogenic viruses whose down-regulation has been seen associated with deep vein thrombosis and cardiovascular diseases. Interestingly, one of these miRNAs, namely miR-20a-5p, whose expression decreases with advancing age, is involved in cytokine signaling, cell differentiation and/or proliferation. We hypothesize that depletion of poorly expressed miRNA could be related with disease severity.

Characterization of the SARS-CoV-2 ExoN (nsp14ExoN-nsp10) complex: implications for its role in viral genome stability and inhibitor identification.

The SARS-CoV-2 coronavirus is the causal agent of the current global pandemic. SARS-CoV-2 belongs to an order, Nidovirales, with very large RNA genomes. It is proposed that the fidelity of coronavirus (CoV) genome replication is aided by an RNA nuclease complex, comprising the non-structural proteins 14 and 10 (nsp14–nsp10), an attractive target for antiviral inhibition. Our results validate reports that the SARS-CoV-2 nsp14–nsp10 complex has RNase activity. Detailed functional characterization reveals nsp14–nsp10 is a versatile nuclease capable of digesting a wide variety of RNA structures, including those with a blocked 3′-terminus. Consistent with a role in maintaining viral genome integrity during replication, we find that nsp14–nsp10 activity is enhanced by the viral RNA-dependent RNA polymerase complex (RdRp) consisting of nsp12–nsp7–nsp8 (nsp12–7–8) and demonstrate that this stimulation is mediated by nsp8. We propose that the role of nsp14–nsp10 in maintaining replication fidelity goes beyond classical proofreading by purging the nascent replicating RNA strand of a range of potentially replication-terminating aberrations. Using our developed assays, we identify drug and drug-like molecules that inhibit nsp14–nsp10, including the known SARS-CoV-2 major protease (Mpro) inhibitor ebselen and the HIV integrase inhibitor raltegravir, revealing the potential for multifunctional inhibitors in COVID-19 treatment.

Genomic Characterization of SARS-CoV2 from Peshawar Pakistan Using Next-Generation Sequencing.

This study aimed to characterize the whole genome of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) isolated from an oropharyngeal swab specimen of a Pashtun Pakistani patient using next-generation sequencing. Upon comparing the SARS-CoV2 genome to the reference genome, a total of 10 genetic variants were identified. Among the 10 genetic variants, 1 missense mutation (c.1139A > G, p.Lys292Glu) in the Open Reading Frame 1ab (ORF1ab) positioned at 112 in the non-structural protein 2 (NSP2) was found to be unique. Phylogenetic analysis (n = 84) revealed that the current SARS-CoV2 genome was closely clustered with 8 Pakistani strains belonging to Punjab, Federal Capital, Azad Jammu and Kashmir (AJK), and Khyber Pakhtunkhwa (KP). In addition, the current SARS-CoV2 genome was very similar to the genome of SARS-CoV2 reported from Guam, Taiwan, India, the USA, and France. Overall, this study reports a slight mismatch in the SARS-CoV2 genome, indicating the presence of a single unique missense mutation. However, phylogenetic analysis revealed that the current SARS-CoV2 genome was closely clustered with 8 other Pakistani strains.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00284-021-02743-y.

The highly conserved RNA-binding specificity of nucleocapsid protein facilitates the identification of drugs with broad anti-coronavirus activity

The binding of SARS-CoV-2 nucleocapsid (N) protein to both the 5′- and 3′-ends of genomic RNA has different implications arising from its binding to the central region during virion assembly. However, the mechanism underlying selective binding remains unknown. Herein, we performed the high-throughput RNA-SELEX (HTR-SELEX) to determine the RNA-binding specificity of the N proteins of various SARS-CoV-2 variants as well as other β-coronaviruses and showed that N proteins could bind two unrelated sequences, both of which were highly conserved across all variants and species. Interestingly, both sequences are virtually absent from the human transcriptome; however, they exhibit a highly enriched, mutually complementary distribution in the coronavirus genome, highlighting their varied functions in genome packaging. Our results provide mechanistic insights into viral genome packaging, thereby increasing the feasibility of developing drugs with broad-spectrum anti-coronavirus activity by targeting RNA binding by N proteins.

Evolutionary trend of SARS-CoV-2 inferred by the homopolymeric nucleotide repeats

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current global COVID-19 pandemic, in which millions of lives have been lost. Understanding the zoonotic evolution of the coronavirus may provide insights for developing effective vaccines, monitoring the transmission trends, and preventing new zoonotic infections. Homopolymeric nucleotide repeats (HP), the most simple tandem repeats, are a ubiquitous feature of eukaryotic genomes. Yet the HP distributions and roles in coronavirus genome evolution are poorly investigated. In this study, we characterize the HP distributions and trends in the genomes of bat and human coronaviruses and SARS-CoV-2 variants. The results show that the SARS-CoV-2 genome is abundant in HPs, and has augmented HP contents during evolution. Especially, the disparity of HP poly-(A/T) and ploy-(C/G) of coronaviruses increases during the evolution in human hosts. The disparity of HP poly-(A/T) and ploy-(C/G) is correlated to host adaptation and the virulence level of the coronaviruses. Therefore, we propose that the HP disparity can be a quantitative measure for the zoonotic evolution levels of coronaviruses. Peculiarly, the HP disparity measure infers that SARS-CoV-2 Omicron variants have a high disparity of HP poly-(A/T) and ploy-(C/G), suggesting a high adaption to the human hosts.