Viral Genome Sequences Research Articles

Shift in Demographic Involvement and Clinical Characteristics of COVID-19 From Wild-Type SARS-CoV-2 to the Delta Variant in the Indian Population: In Silico Analysis.

The Delta variant (B.1.617.2) was considered the most dangerous SARS-CoV-2 strain; however, in-depth studies on its impact based on demographic and clinical characteristics of COVID-19 are scarce. We aimed to investigate the shift in demographic and clinical characteristics of the COVID-19 pandemic with the emergence of the SARS-CoV-2 Delta variant compared with the wild-type (WT) strain (B.1). A cross-sectional study of COVID-19 cases in the Indian population caused by the WT strain (B.1) and Delta variant of SARS-CoV-2 was performed. The viral genomic sequence metadata containing demographic, vaccination, and patient status details (N=9500, NDelta=6238, NWT=3262) were statistically analyzed. With the Delta variant, in comparison with the WT strain, a higher proportion of young individuals (<20 years) were infected (0-9 years: Delta: 281/6238, 4.5% vs B.1: 75/3262, 2.3%; 10-19 years: Delta: 562/6238, 9% vs B.1: 229/3262, 7%; P<.001). The proportion of women contracting infection increased (Delta: 2557/6238, 41% vs B.1: 1174/3262, 36%; P<.001). However, it decreased for men (Delta: 3681/6238, 59% vs B.1: 2088/3262, 64%; P<.001). An increased proportion of the young population developed symptomatic illness and were hospitalized (Delta: 27/262, 10.3% vs B.1: 5/130, 3.8%; P=.02). Moreover, an increased proportion of the women (albeit not men) from the young (Delta: 37/262, 14.1% vs B.1: 4/130, 3.1%; P<.001) and adult (Delta: 197/262, 75.2% vs B.1: 72/130, 55.4%; P<.001) groups developed symptomatic illness and were hospitalized. The mean age of men and women who contracted infection (Delta: men=37.9, SD 17.2 years; women=36.6, SD 17.6 years; P<.001; B.1: men=39.6, SD 16.9 years; women=40.1, SD 17.4 years; P<.001) as well as developing symptoms or being hospitalized (Delta: men=39.6, SD 17.4 years; women=35.6, SD 16.9 years, P<.001; B.1: men=47, SD 18 years; women=49.5, SD 20.9 years, P<.001) were considerably lower with the Delta variant than the B.1 strain. The total mortality was about 1.8 times higher with the Delta variant than with the WT strain. With the Delta variant, compared with B.1, mortality decreased for men (Delta: 58/85, 68% vs B.1: 15/20, 75%; P<.001); in contrast, it increased for women (Delta: 27/85, 32% vs B.1: 5/20, 25%; P<.001). The odds of death increased with age, irrespective of sex (odds ratio 3.034, 95% CI 1.7-5.2, P<.001). Frequent postvaccination infections (24/6238) occurred with the Delta variant following complete doses. The increased involvement of young people and women, the lower mean age for illness, higher mortality, and frequent postvaccination infections were significant epidemiological concerns with the Delta variant.

From the discovery of a novel arepavirus in diseased arecanut palms (Areca catechu L.) in India to the identification of known and novel arepaviruses in bee and plant transcriptomes through data-mining

Arecanut palm is a commercially important plantation crop valued for its nut. In this investigation, we report the discovery of a putative novel arepavirus, named areca palm necrotic ringspot virus 2 (ANRSV2), in necrotic ringspot diseased areca palms in Bantwal, Dakshina Kannada, Karnataka, India through RNA-sequencing and transmission electron microscopy. Further, the presence of ANRSV2 in the diseased samples was confirmed through reverse transcriptase-polymerase chain reaction assays. In addition, by mining public domain transcriptome data for arepaviral sequences, we identified a putative novel arepavirus in Psychotria rubra, a non-palm host. We recovered the genome sequences of the areca palm necrotic ringspot virus in honey bees, tomato, Onobrychis viciifolia, and Rhamnus heterophylla. These findings broaden our comprehension of arepaviral diversity and host range, and suggest an intriguing possibility of pollen-mediated arepaviral transmission that necessitates empirical validation. Further studies are needed to understand the biology of identified putative novel arepaviruses.

ILKD: An Incremental Learning and Knowledge Distillation Framework for Coronavirus Risk Prediction

Abstract The coronavirus pandemic has seriously affected public health and social order. Prediction methods based on machine learning can identify the infectivity phenotype and pandemic risk of coronavirus. Currently, six types of coronaviruses that infect humans have been discovered, with significant differences in viral genome sequences. Continuous genetic variation of the virus will lead to reduced performance of machine learning models and potential learning forgetting. To solve this challenge, we propose an incremental learning and knowledge distillation framework (ILKD). First, we employ Dna2Vec to extract virus features and encode the virus sequence into virus feature vector. Second, we use hierarchical clustering to continuously identify new coronavirus groups. Third, ILKD employ a combined strategy of incremental learning and knowledge distillation to transform the Back Propagation (BP) neural network to continuously learn and predict the phenotypes of human-to-human coronavirus infection. Experimental results show that ILKD can effectively alleviate the learning forgetting phenomenon. Further analysis reveals ILKD has better performance than other incremental learning models, and has important public health application value.

Viral whole genome sequencing reveals high variations in APOBEC3 editing between HPV risk categories.

High-risk human papillomavirus (HPV) infections are responsible for cervical cancer. However, little is known about the differences between HPV types and risk categories regarding their genetic diversity and particularly APOBEC3-induced mutations - which contribute to the innate immune response to HPV. Using a capture-based next-generation sequencing, 156 HPV whole genome sequences covering 43 HPV types were generated from paired cervical and anal swabs of 30 Togolese female sex workers (FSWs) sampled in 2017. Genetic diversity and APOBEC3-induced mutations were assessed at the viral whole genome and gene levels. Thirty-four pairwise sequence comparisons covering 24 HPV types in cervical and anal swabs revealed identical infections in the two anatomical sites. Differences in genetic diversity among HPV types was observed between patients. The E6 gene was significantly less conserved in low-risk HPVs (lrHPVs) compared to high-risk HPVs (hrHPVs) (p = 0.009). APOBEC3-induced mutations were found to be more common in lrHPVs than in hrHPVs (p = 0.005), supported by our data and by using large HPV sequence collections from the GenBank database. Focusing on the most common lrHPVs 6 and 11 and hrHPVs 16 and 18, APOBEC3-induced mutations were predominantly found in the E4 and E6 genes in lrHPVs, but were almost absent in these genes in hrHPVs. The variable APOBEC3 mutational signatures could contribute to the different oncogenic potentials between HPVs. Further studies are needed to conclusively determine whether APOBEC3 editing levels are associated to the carcinogenic potential of HPVs at the type and sublineage scales.

Presumed Transmission of 2 Distinct Monkeypox Virus Variants from Central African Republic to Democratic Republic of the Congo.

We linked 4 mpox cases in South Ubangi, Democratic Republic of the Congo, to transboundary transmission from Central African Republic. Viral genome sequencing demonstrated that the monkeypox virus sequences belonged to distinct clusters of subclade Ia. This finding demonstrates the borderless nature of mpox and highlights the need for vigilant regional surveillance.

Effect of Simulated Cosmic Radiation on Cytomegalovirus Reactivation and Lytic Replication.

Human exploration of the solar system will expose crew members to galactic cosmic radiation (GCR), with a potential for adverse health effects. GCR particles (protons and ions) move at nearly the speed of light and easily penetrate space station walls, as well as the human body. Previously, we have shown reactivation of latent herpesviruses, including herpes simplex virus, Varicella zoster virus, Epstein-Barr virus, and cytomegalovirus (CMV), during stays at the International Space Station. Given the prevalence of latent CMV and the known propensity of space radiation to cause alterations in many cellular processes, we undertook this study to understand the role of GCR in reactivating latent CMV. Latently infected Kasumi cells with CMV were irradiated with 137Cs gamma rays, 150 MeV protons, 600 MeV/n carbon ions, 600 MeV/n iron ions, proton ions, and simulated GCR. The CMV copy number increased significantly in the cells exposed to radiation as compared with the non-irradiated controls. Viral genome sequencing did not reveal significant nucleotide differences among the compared groups. However, transcriptome analysis showed the upregulation of transcription of the UL49 ORF, implicating it in the switch from latent to lytic replication. These findings support our hypothesis that GCR may be a strong contributor to the reactivation of CMV infection seen in ISS crew members.

Reducing amplification cycles to improve the coverage of influenza A virus genome sequencing in heterosubtypic co-infection

This study delineates the enhancement of a Reverse Transcription Polymerase Chain Reaction (RT-PCR) method for the amplification of the complete genome of the influenza A virus during heterosubtypic co-infection, relying on the amplification of intact gene segments. The precision of the method was assessed using all amplicons, which underwent both capillary electrophoresis and DNA sequencing. Five samples featuring co-infection of Influenza A viruses with H1N1 and H3N2 subtypes were evaluated. The improved strategy successfully amplified all eight segments of H3N2 strains in four samples, and the entire genome of H1N1 strains in three samples.

A Review on Characterization of SARS-COVID-19-2 Omicron (B.1.1.529) and JN.1 Variant of Concern and its Global Perspective

In this review, we summarize the researches on animal reservoirs of the SARS corona virus (SARS-CoV). Masked palm civets had been suspected because the foundation of the SARS outbreak in 2003 and turned into showed because the direct foundation of SARS instances with slight symptom in 2004. Sequence evaluation of the SARS-CoV-like virus in masked palm civets indicated that they had been exceedingly homologous to human SARS-CoV with, identification over 99.6%, indicating the virus has now no longer been circulating with inside the population of masked palm civets for a totally lengthy time. Alignment of 10 entire viral genome sequences from masked palm civets with the ones of human SARS-CoVs found out 26 conserved single- nucleotide variations (SNVs) with inside the viruses from masked palm civets. These conserved SNVs had been step by step misplaced from the genomes of viruses remoted from the early section to overdue section human sufferers of the 2003 SARS epidemic. In 2005, horseshoe bats had been recognized because the herbal reservoir of a set of corona viruses which can be distantly associated with SARS-CoV. The genome sequences of bat SARS-like corona virus had approximately 88–92% identification with that of the SARS-CoV. The incidence of antibodies and viral RNA in special bat species and the traits of the bat SARS-like corona virus had been elucidated. Apart from masked palm civets and bats, 29 different animal species were examined for the SARS-CoV, and the outcomes are summarized on this paper. Corona viruses (CoV) are a massive own circle of relatives of viruses inflicting a spectrum of sickness starting from the 22 not unusual place bloodless to greater intense illnesses as Middle East Respiratory Syndrome (MERS-CoV) and 23 Severe Acute Respiratory Syndrome (SARS-CoV). The current outbreak of corona virus sickness 24 2019 (COVID-19) has come to be a public fitness emergency worldwide. SARS-CoV-2, the virus 25 accountable for COVID-19, is unfolded through human- to-human transmission through droplets or direct 26contact.

HLA-C Peptide Repertoires as Predictors of Clinical Response during Early SARS-CoV-2 Infection.

The human leukocyte antigen (HLA) system plays a pivotal role in the immune response to viral infections, mediating the presentation of viral peptides to T cells and influencing both the strength and specificity of the host immune response. Variations in HLA genotypes across individuals lead to differences in susceptibility to viral infection and severity of illness. This study uses observations from the early phase of the COVID-19 pandemic to explore how specific HLA class I molecules affect clinical responses to SARS-CoV-2 infection. By analyzing paired high-resolution HLA types and viral genomic sequences from 60 patients, we assess the relationship between predicted HLA class I peptide binding repertoires and infection severity as measured by the sequential organ failure assessment score. This approach leverages functional convergence across HLA-C alleles to identify relationships that may otherwise be inaccessible due to allelic diversity and limitations in sample size. Surprisingly, our findings show that severely symptomatic infection in this cohort is associated with disproportionately abundant binding of SARS-CoV-2 structural and non-structural protein epitopes by patient HLA-C molecules. In addition, the extent of overlap between a given patient's predicted HLA-C and HLA-A peptide binding repertoires correlates with worse prognoses in this cohort. The findings highlight immunologic mechanisms linking HLA-C molecules with the human response to viral pathogens that warrant further investigation.

Co-circulation of monkeypox virus subclades Ia and Ib in Kinshasa Province, Democratic Republic of the Congo, July to August 2024.

Between January and August 2024, mpox cases have been reported in nearly all provinces of the Democratic Republic of the Congo (DRC). Monkeypox virus genome sequences were obtained from 11 mpox cases' samples, collected in July-August 2024 in several health zones of Kinshasa. Characterisation of the sequences showed subclades Ia and Ib co-circulating in the Limete health zone, while phylogenetic analyses suggested multiple introductions of the two subclades in Kinshasa. This illustrates the growing complexity of Clade I mpox outbreaks in DRC.

Epidemiology and genetic characterization of influenza viruses circulating in Bhutan in 2022.

Influenza (Flu) causes considerable morbidity and mortality globally, and in Bhutan, Flu viruses are a leading cause of acute respiratory infection and cause outbreaks during Flu seasons. In this study, we aim to analyze the epidemiology and the genetic characterization of Flu viruses circulated in Bhutan in 2022. Respiratory specimens were collected from patients who meet the case definition for influenza-like illness (ILI) and severe acute respiratory infection (SARI) from sentinel sites. Specimens were tested for Flu and SARS-CoV-2 viruses by RT-PCR using the Multiplex Assay. Selected positive specimens were utilized for Flu viral genome sequencing by next-generation sequencing. Descriptive analysis was performed on patient demographics to see the proportion of Flu-associated ILI and SARI. All data were analyzed using Epi Info7 and QGIS 3.16 software. A weekly average of 16.2 ILI cases per 1000 outpatient visits and 18 SARI cases per 1000 admitted cases were reported in 2022. The median age among ILI was 12 years (IQR: 5-28) and SARI was 6.2 (IQR: 2.5-15) years. Flu A(H3N2) (70.2%) subtype was the most predominant circulating strain. Flu A(H1N1)pdm09 and Flu B viruses belonged to subclades that were mismatched to the vaccine strains recommended for the 2021-2022 season but matched the vaccine strain for the 2022-2023 season with vaccine efficacy 85.14% and 88.07% respectively. Flu A(H3N2) virus belonged to two subclades which differed from the vaccine strains recommended in both the 2021-2022 and 2022-2023 seasons with vaccine efficacy 68.28%. Flu virus positivity rates were substantially elevated during the Flu season in 2022 compared to 2021. Flu A(H3N2) subtype was the most predominant circulating strain in the country and globally. Genetic characterization of the Flu viruses in Bhutan showed a close relatedness of high vaccine efficacy with the vaccine strain that WHO recommended for the 2022-23 season.

Molecular characterisation of influenza B virus from the 2017/18 season in primary models of the human lung reveals improved adaptation to the lower respiratory tract

ABSTRACT The 2017/18 influenza season was characterized by unusual high numbers of severe infections and hospitalizations. Instead of influenza A viruses, this season was dominated by infections with influenza B viruses of the Yamagata lineage. While this IBV/Yam dominance was associated with a vaccine mismatch, a contribution of virus intrinsic features to the clinical severity of the infections was speculated. Here, we performed a molecular and phenotypic characterization of three IBV isolates from patients with severe flu symptoms in 2018 and compared it to an IBV/Yam isolate from 2016 using experimental models of increasing complexity, including human lung explants, lung organoids, and alveolar macrophages. Viral genome sequencing revealed the presence of clade but also isolate specific mutations in all viral genes, except NP, M1, and NEP. Comparative replication kinetics in different cell lines provided further evidence for improved replication fitness, tolerance towards higher temperatures, and the development of immune evasion mechanisms by the 2018 IBV isolates. Most importantly, immunohistochemistry of infected human lung explants revealed an impressively altered cell tropism, extending from AT2 to AT1 cells and macrophages. Finally, transcriptomics of infected human lung explants demonstrated significantly reduced amounts of type I and type III IFNs by the 2018 IBV isolate, supporting the existence of additional immune evasion mechanisms. Our results show that the severeness of the 2017/18 Flu season was not only the result of a vaccine mismatch but was also facilitated by improved adaptation of the circulating IBV strains to the environment of the human lower respiratory tract.

SARS-CoV-2 Variants May Affect Saliva RT-PCR Assay Sensitivity.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants demonstrate predilection for different regions of the respiratory tract. While saliva-based reverse transcription-polymerase chain reaction (RT-PCR) testing is a convenient, cost-effective alternative to nasopharyngeal swabs (NPS), few studies to date have investigated whether saliva sensitivity differs across variants of concern. SARS-CoV-2 RT-PCR was performed on paired NPS and saliva specimens collected from individuals with acute coronavirus disease 2019 (COVID-19) symptoms or exposure to a COVID-19 household contact. Viral genome sequencing of NPS specimens and Los Angeles County surveillance data were used to determine the variant of infection. Saliva sensitivity was calculated using NPS-positive RT-PCR as the reference standard. Factors contributing to the likelihood of saliva SARS-CoV-2 RT-PCR positivity were evaluated with univariate and multivariable analyses. Between June 2020 and December 2022, 548 saliva samples paired with SARS-CoV-2 positive NPS samples were tested by RT-PCR. Overall, saliva sensitivity for SARS-CoV-2 detection was 61.7% (95% CI, 57.6%-65.7%). Sensitivity was highest with Delta infection (79.6%) compared to pre-Delta (58.5%) and Omicron (61.5%) (P = 0.003 and 0.01, respectively). Saliva sensitivity was higher in symptomatic individuals across all variants compared to asymptomatic cases [pre-Delta 80.6% vs 48.3% (P < 0.001), Delta 100% vs 72.5% (P = 0.03), Omicron 78.7% vs 51.2% (P < 0.001)]. Infection with Delta, symptoms, and high NPS viral load were independently associated with 2.99-, 3.45-, and 4.0-fold higher odds of SARS-CoV-2 detection by saliva-based RT-PCR (P = 0.004, <0.001, and <0.001), respectively. As new variants emerge, evaluating saliva-based testing approaches may be crucial to ensure effective virus detection.

Molecular epidemiology of SARS-CoV-2 genome sentinel surveillance in commercial COVID-19 testing sites targeting asymptomatic individuals during Japan’s seventh epidemic wave

Eight peaks of coronavirus disease 2019 (COVID-19) outbreak occurred in Japan, each associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern. The National Epidemiological Surveillance of Infectious Diseases (NESID) analyzed viral genome sequences from symptomatic patients and submitted the results to GISAID. Meanwhile, commercial testing services occasionally sequence samples from asymptomatic individuals. We compared a total of 1248 SARS-CoV-2 full-genome sequences obtained from the SB Coronavirus Inspection Center Corp. (SBCVIC) during Japan’s seventh wave, which was dominated by Omicron variants, with 1764 sequences obtained in Japan from GISAID during the same period using chronological phylogenies and molecular transmission networks. The number of SBCVIC sequences was consistent with the number of cases reported by NESID. The SBCVIC detected a shift in the PANGO lineage from BA.2 to BA.5 earlier than that of GISAID. BA.2 lineages from the SBCVIC were distributed at different locations in the transmission network dominated by GISAID entries, whereas BA.5 lineages from SBCVIC and GISAID often formed distinct subclusters. Test-based sentinel surveillance of asymptomatic individuals may be a more manageable approach compared to notifiable disease surveillance; however, it may not necessarily capture all infection populations throughout Japan.

A Novel Natural Graph for Efficient Clustering of Virus Genome Sequences

Background: This study addresses the need for analyzing viral genome sequences and understanding their genetic relationships. The focus is on introducing a novel natural graph approach as a solution. Objective: The objective of this study is to demonstrate the effectiveness and advantages of the proposed natural graph approach in clustering viral genome sequences into distinct clades, subtypes, or districts. Additionally, the aim is to explore its interpretability, potential applications, and implications for pandemic control and public health interventions. Methods: The study utilizes the proposed natural graph algorithm to cluster viral genome sequences. The results are compared with existing methods and multidimensional scaling to evaluate the performance and effectiveness of the approach. Results: The natural graph approach successfully clusters viral genome sequences, providing valuable insights into viral evolution and transmission dynamics. The ability to generate directed connections between nodes enhances the interpretability of the results, facilitating the investigation of transmission pathways and viral fitness. Conclusion: The findings highlight the potential applications of the natural graph algorithm in pandemic control, transmission tracing, and vaccine design. Future research directions may involve scaling up the analysis to larger datasets and incorporating additional genetic features for improved resolution. : The natural graph approach presents a promising tool for viral genomics research with implications for public health interventions.

Whole genome sequencing of equine influenza virus to enhance surveillance in the United Kingdom

Whole genome sequencing of equine influenza virus to enhance surveillance in the United Kingdom

Full genomic sequence characterization of the chikungunya virus from an imported case with serum viral concentration below culturable level

Chikungunya virus (CHIKV) infection, responsible for chikungunya fever and occasionally severe symptoms, has emerged as an increasing global health concern following several large-scale outbreaks from Africa, Asia, Europe, and America. Over the past two decades, South and Southeast Asia regions have gradually become hot spots for outbreaks involving multiple CHIKV lineages. In China, most CHIKV infections are imported, making it crucial to trace the origins and transmission routes for effective prevention and control. In January 2024, a case of imported chikungunya fever was confirmed in Guangzhou City, Guangdong Province, China. However, the serum CHIKV viral concentration was too low for cultivation [reverse transcription-polymerase chain reaction (RT-PCR) detection, cycle threshold = 32.62]. Despite this, we successfully obtained the viral genome sequence directly from the whole blood sample using an optimized metatranscriptomic sequencing strategy, achieving a full-length viral genome with an average depth of 54.3X. Further analysis confirmed that the CHIKV virus belonged to the Asian lineage, traced to Timor-Leste, where an endemic CHIKV outbreak had been reported in January 2024, consistent with the patient’s travel history. Finally, we analyzed genetic evolutionary trends and amino acid site variations. This study highlights the identification of a CHIKV infection origin using direct whole-blood metatranscriptomic sequencing, a valuable method for rapidly sequencing low viral-load samples.

Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2.

Public health researchers and practitioners commonly infer phylogenies from viral genome sequences to understand transmission dynamics and identify clusters of genetically-related samples. However, viruses that reassort or recombine violate phylogenetic assumptions and require more sophisticated methods. Even when phylogenies are appropriate, they can be unnecessary or difficult to interpret without specialty knowledge. For example, pairwise distances between sequences can be enough to identify clusters of related samples or assign new samples to existing phylogenetic clusters. In this work, we tested whether dimensionality reduction methods could capture known genetic groups within two human pathogenic viruses that cause substantial human morbidity and mortality and frequently reassort or recombine, respectively: seasonal influenza A/H3N2 and SARS-CoV-2. We applied principal component analysis (PCA), multidimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection (UMAP) to sequences with well-defined phylogenetic clades and either reassortment (H3N2) or recombination (SARS-CoV-2). For each low-dimensional embedding of sequences, we calculated the correlation between pairwise genetic and Euclidean distances in the embedding and applied a hierarchical clustering method to identify clusters in the embedding. We measured the accuracy of clusters compared to previously defined phylogenetic clades, reassortment clusters, or recombinant lineages. We found that MDS embeddings accurately represented pairwise genetic distances including the intermediate placement of recombinant SARS-CoV-2 lineages between parental lineages. Clusters from t-SNE embeddings accurately recapitulated known phylogenetic clades, H3N2 reassortment groups, and SARS-CoV-2 recombinant lineages. We show that simple statistical methods without a biological model can accurately represent known genetic relationships for relevant human pathogenic viruses. Our open source implementation of these methods for analysis of viral genome sequences can be easily applied when phylogenetic methods are either unnecessary or inappropriate.

Genome microsatellite signature analysis in Adenoviridae family of viruses

Simple sequence repeats (SSRs) are present across both coding & non-coding regions of the genomes of all organisms with diversity in incidence, complexity, and repetition. The present study is focused on Adenoviridae which are non-enveloped viruses consisting of linear double-stranded DNA genome. The members of Adenoviridae are known to cause respiratory illnesses like the common cold (cough, runny nose, mild fever), pneumonia (occasionally), keratoconjunctivitis (infection in the eye known as pink eye), croup and cystitis (inflammation of the bladder). Our investigation aims to extract and analyse SSRs from 68 Adenoviridae genomes. Virus genome sequences were retrieved from NCBI and SSRs extracted from MISA. ETE3 and iTOL were used for the phylogenetic tree construction, annotation and visualization. The genome length of Adenoviridae genomes ranged from 26163 bp to 45667 bp while GC content varied from 33.6 % to 66.9 %. Genome wide analysis revealed a total incidence of 9861 SSRs and 793 cSSRs. The minimum and maximum range of SSR incidence is 112 (A67) to 203 (A61) respectively. The most prevalent mono, di and tri-SSR motif is “A”, “GC/CG” and “GAG/CTC” comprised of 1177, 1859 and 201 occurrences respectively. About 78 % SSRs are present in the coding region in the studied genomes. In terms of protein specific distribution, DNA polymerase enzyme had the highest incidence of 485 SSRs. The presence of mono-SSRs in the A/T region is a marker for host determination and divergence. The average mono-SSRs present in A/T region is 67.14 % and it ranged from 16.22 % to 99.11 %. The high prevalence of mono-SSRs in the A/T region was associated with human and related species as hosts. Further, the clustering of viruses as per their hosts was observed in the phylogenetic tree suggesting the role of host in viral evolution. The presence of unique and conserved cSSRs as genome markers has also been highlighted.

The Australian Biosecurity Genomic Database: a new resource for high-throughput sequencing analysis based on the National Notifiable Disease List of Terrestrial Animals.

The Australian Biosecurity Genomic Database (ABGD) is a curated collection of reference viral genome sequences based on the Australian National Notifiable Disease List of Terrestrial Animals. It was created to facilitate the screening of high-throughput sequencing (HTS) data for the potential presence of viruses associated with notifiable disease. The database includes a single verified sequence (the exemplar species sequence, where relevant) for each of the 60 virus species across 21 viral families that are associated with or cause these notifiable diseases, as recognized by the World Organisation for Animal Health. The open-source ABGD on GitHub provides usage guidance documents and is intended to support building a culture in Australian HTS communities that promotes the use of quality-assured, standardized, and verified databases for Australia's national biosecurity interests. Future expansion of the database will include the addition of more strains or subtypes for highly variable viruses, viruses causing diseases of aquatic animals, and genomes of other types of pathogens associated with notifiable diseases, such as bacteria. Database URL: https://github.com/ausbiopathgenDB/AustralianBiosecurityGenomicDatabase.