What is the result of phylogenetic analysis of SARS-CoV-2 genome sequence?

COVID-19 has effectively spread worldwide. As of May 2020, Turkey is among the top ten countries with the most cases. A comprehensive genomic characterization of the virus isolates in Turkey is yet to be carried out. Here, we built a phylogenetic tree with globally obtained 15,277 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes. We identified the subtypes based on the phylogenetic clustering in comparison with the previously annotated classifications. We performed a phylogenetic analysis of the first thirty SARS-CoV-2 genomes isolated and sequenced in Turkey. We suggest that the first introduction of the virus to the country is earlier than the first reported case of infection. Virus genomes isolated from Turkey are dispersed among most types in the phylogenetic tree. We find two of the seventeen sub-clusters enriched with the isolates of Turkey, which likely have spread expansively in the country. Finally, we traced virus genomes based on their phylogenetic placements. This analysis suggested multiple independent international introductions of the virus and revealed a hub for the inland transmission. We released a web application to track the global and interprovincial virus spread of the isolates from Turkey in comparison to thousands of genomes worldwide.

Phylogenetic Analysis of SARS-CoV-2 Genomes in Turkey

Background The origin of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is still a debatable topic. The association of the virus spread from the market is supported by the close relation of genome sequences of environmental surface samples with virus samples from earliest patients by phylogenetic analysis. Objectives To have an insight into the SARS-CoV-2 genome sequences reported from India for better understanding on their epidemiology and virulence. Methods Genome sequences of Indian isolates of SARS-CoV-2 were analyzed to understand their phylogeny and divergence with respect to other isolates reported from other countries. Amino acid sequences of individual open reading frames (ORFs) from SARS-CoV-2 Indian isolates were aligned with sequences of isolates reported from other countries to identify the mutations occurred in Indian isolates. Results Our analysis suggests that Indian SARS-CoV-2 isolates are closely related to isolates reported from other parts of the world. Most ORFs are highly conserved; mutations were also detected in some ORFs. We found that most isolates reported from India have key mutations at 614th position of the S protein and 84th position of the ORF 8, which has been reported to be associated with high virulence and high transmission rate. Conclusion An attempt was made to understand the SARS-CoV-2 virus reported from India. SARS-CoV-2 reported from India was closely similar to other SARS-CoV-2 reported from other parts of the world, which suggests that vaccines and other therapeutic methods generated from other countries might work well in India. In addition, available sequence data suggest that majority of Indian isolates are capable of high transmission and virulence.

Genome analysis of SARS-CoV-2 isolates occurring in India: Present scenario.

COVID-19 has effectively spread worldwide. As of May 2020, Turkey is among the top ten countries with the most cases. A comprehensive genomic characterization of the virus isolates in Turkey is yet to be carried out. Here, we built a phylogenetic tree with globally obtained 15,277 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes. We identified the subtypes based on the phylogenetic clustering in comparison with the previously annotated classifications. We performed a phylogenetic analysis of the first 30 SARS-CoV-2 genomes isolated and sequenced in Turkey. We suggest that the first introduction of the virus to the country is earlier than the first reported case of infection. Virus genomes isolated from Turkey are dispersed among most types in the phylogenetic tree. We find 2 of the seventeen subclusters enriched with the isolates of Turkey, which likely have spread expansively in the country. Finally, we traced virus genomes based on their phylogenetic placements. This analysis suggested multiple independent international introductions of the virus and revealed a hub for the inland transmission. We released a web application to track the global and interprovincial virus spread of the isolates from Turkey in comparison to thousands of genomes worldwide.

Phylogenetic analysis of SARS-CoV-2 genomes in Turkey

Background: The origin of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is still a debatable topic. The association of the virus spread from the market is supported by the close relation of genome sequences of environmental surface samples with virus samples from earliest patients by phylogenetic analysis. Objectives: To have an insight into the SARS-CoV-2 genome sequences reported from India for better understanding on their epidemiology and virulence. Methods: Genome sequences of Indian isolates of SARS-CoV-2 were analyzed to understand their phylogeny and divergence with respect to other isolates reported from other countries. Amino acid sequences of individual open reading frames (ORFs) from SARS-CoV-2 Indian isolates were aligned with sequences of isolates reported from other countries to identify the mutations occurred in Indian isolates. Results: Our analysis suggests that Indian SARS-CoV-2 isolates are closely related to isolates reported from other parts of the world. Most ORFs are highly conserved; mutations were also detected in some ORFs. We found that most isolates reported from India have key mutations at 614th position of the S protein and 84th position of the ORF 8, which has been reported to be associated with high virulence and high transmission rate. Conclusion: An attempt was made to understand the SARS-CoV-2 virus reported from India. SARS-CoV-2 reported from India was closely similar to other SARS-CoV-2 reported from other parts of the world, which suggests that vaccines and other therapeutic methods generated from other countries might work well in India. In addition, available sequence data suggest that majority of Indian isolates are capable of high transmission and virulence.

Genome analysis of SARS-CoV-2 isolates occurring in India: Present scenario

Over 10,000 viral genome sequences of the SARS-CoV-2 virus have been made readily available during the ongoing coronavirus pandemic since the initial genome sequence of the virus was released on the open access Virological website (http://virological.org/) early on January 11. We utilize the published data on the single stranded RNAs of 11, 132 SARS-CoV-2 patients in the GISAID (Elbe and Buckland-Merrett, 2017; Shu and McCauley, 2017) database, which contains fully or partially sequenced SARS-CoV-2 samples from laboratories around the world. Among many important research questions which are currently being investigated, one aspect pertains to the genetic characterization/classification of the virus. We analyze data on the nucleotide sequencing of the virus and geographic information of a subset of 7, 640 SARS-CoV-2 patients without missing entries that are available in the GISAID database. Instead of modelling the mutation rate, applying phylogenetic tree approaches, etc., we here utilize a model-free clustering approach that compares the viruses at a genome-wide level. We apply principal component analysis to a similarity matrix that compares all pairs of these SARS-CoV-2 nucleotide sequences at all loci simultaneously, using the Jaccard index (Jaccard, 1901; Tan et al., 2005; Prokopenko et al., 2016; Schlauch et al., 2017). Our analysis results of the SARS-CoV-2 genome data illustrates the geographic and chronological progression of the virus, starting from the first cases that were observed in China to the current wave of cases in Europe and North America. We also observe that, based on their sequence data, the SARS-CoV-2 viruses cluster in distinct genetic subgroups. It is the subject of ongoing research to examine whether the genetic subgroup could be related to diseases outcome and its potential implications for vaccine development.

Unsupervised cluster analysis of SARS-CoV-2 genomes reflects its geographic progression and identifies distinct genetic subgroups of SARS-CoV-2 virus

The current global pandemic COVID-19, caused by SARS-CoV-2, has resulted in millions of infections worldwide in a few months. Global efforts to tackle this situation have produced a tremendous body of genomic data, which can be used for tracing transmission routes, characterization of isolates, and monitoring variants with potential for unusual virulence. Several groups have analyzed these genomes using different approaches. However, as new data become available, the research community needs a pipeline to perform a set of routine analyses, that can quickly incorporate new genome sequences and update the analysis reports. We developed a programmatic tool, CoVa, with this objective. It is a fast, accurate and user-friendly utility to perform a variety of genome analyses on hundreds of SARS-CoV-2 sequences. Using CoVa, we define a modified sequence typing nomenclature and identify sites under positive selection. Further analysis identified some peptides and sites showing geographical patterns of selection. Specifically, we show differences in sequence type distribution between sequences from India and those from the rest of the world. We also show that several sites show signatures of positive selection uniquely in sequences from India. Preliminary evolutionary analysis, using features that will be incorporated into CoVa in the near future, show a mutation rate of 7.4 × 10−4 substitutions/site/year, confirm a temporal signal with a November 2019 origin of SARS-CoV-2, and a heterogeneity in the geographical distribution of Indian samples.

SARS-CoV-2 sequence typing, evolution and signatures of selection using CoVa, a Python-based command-line utility

OBJECTIVE: To analyze the evolution and variation of SARS-CoV-2 during the epidemic starting at the end of 2019. METHODS: We downloaded the full-length genome sequence of SARS-CoV-2 from the databases of GISAID and NCBI. Using the software for bioinformatics including MEGA-X, BEAST, and TempEst, we constructed the genomic evolution tree, inferred the time evolution signal of the virus, calculated the tMRCA time of the virus and analyzed the selection pressure of the virus during evolution. RESULTS: The phylogenetic tree showed that SARS-CoV-2 belonged to the Sarbecovirus subgenus of ß Coronavirus genus together with bat coronavirus BetaCoV/bat/Yunnan/RaTG13/2013, bat-SL-CoVZC45, bat-SL-CoVZXC21 and SARS-CoV. The genomic sequences of SARS-CoV-2 isolated from the ongoing epidemic showed a weak time evolution signal with an average tMRCA time of 73 days (95% CI: 38.9-119.3 days). No positive time evolution signal was found between SARS-CoV-2 and BetaCoV/bat/Yunnan/RaTG13/2013, but the former virus had a strong positive temporal evolution relationship with bat-SL-CoVZC45 and SARS-CoV. The major cause for mutations of SARS-CoV-2 was the pressure of purification selection during the epidemic. CONCLUSIONS: SARS-CoV-2 may have emerged as early as November, 2019, originating most likely from bat-associated coronavirus. This finding may provide evidence for tracing the sources and evolution of the virus.

[Analysis of variation and evolution of SARS-CoV-2 genome]

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been growing exponentially, affecting over 4 million people and causing enormous distress to economies and societies worldwide. A plethora of analyses based on viral sequences has already been published both in scientific journals and through non-peer-reviewed channels to investigate the genetic heterogeneity and spatiotemporal dissemination of SARS-CoV-2. However, a systematic investigation of phylogenetic information and sampling bias in the available data is lacking. Although the number of available genome sequences of SARS-CoV-2 is growing daily and the sequences show increasing phylogenetic information, country-specific data still present severe limitations and should be interpreted with caution. OBJECTIVE: The objective of this study was to determine the quality of the currently available SARS-CoV-2 full genome data in terms of sampling bias as well as phylogenetic and temporal signals to inform and guide the scientific community. METHODS: We used maximum likelihood-based methods to assess the presence of sufficient information for robust phylogenetic and phylogeographic studies in several SARS-CoV-2 sequence alignments assembled from GISAID (Global Initiative on Sharing All Influenza Data) data released between March and April 2020. RESULTS: Although the number of high-quality full genomes is growing daily, and sequence data released in April 2020 contain sufficient phylogenetic information to allow reliable inference of phylogenetic relationships, country-specific SARS-CoV-2 data sets still present severe limitations. CONCLUSIONS: At the present time, studies assessing within-country spread or transmission clusters should be considered preliminary or hypothesis-generating at best. Hence, current reports should be interpreted with caution, and concerted efforts should continue to increase the number and quality of sequences required for robust tracing of the epidemic.

A Snapshot of SARS-CoV-2 Genome Availability up to April 2020 and its Implications: Data Analysis

OBJECTIVE To analyze the evolution and variation of SARS-CoV-2 during the epidemic starting at the end of 2019. METHODS We downloaded the full-length genome sequence of SARS-CoV-2 from the databases of GISAID and NCBI. Using the software for bioinformatics including MEGA-X, BEAST, and TempEst, we constructed the genomic evolution tree, inferred the time evolution signal of the virus, calculated the tMRCA time of the virus and analyzed the selection pressure of the virus during evolution. RESULTS The phylogenetic tree showed that SARS-CoV-2 belonged to the Sarbecovirus subgenus of β Coronavirus genus together with bat coronavirus BetaCoV/bat/Yunnan/RaTG13/2013, bat-SL-CoVZC45, bat-SL-CoVZXC21 and SARS-CoV. The genomic sequences of SARS-CoV-2 isolated from the ongoing epidemic showed a weak time evolution signal with an average tMRCA time of 73 days (95% CI: 38.9-119.3 days). No positive time evolution signal was found between SARS-CoV-2 and BetaCoV/bat/Yunnan/RaTG13/2013, but the former virus had a strong positive temporal evolution relationship with bat-SL-CoVZC45 and SARS-CoV. The major cause for mutations of SARS-CoV-2 was the pressure of purification selection during the epidemic. CONCLUSIONS SARS-CoV-2 may have emerged as early as November, 2019, originating most likely from bat-associated coronavirus. This finding may provide evidence for tracing the sources and evolution of the virus.

[Analysis of variation and evolution of SARS-CoV-2 genome].

Impact of mutations on the evolution of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) are needed for ongoing global efforts to track and trace the current pandemic, in order to enact effective prevention and treatment options. SARS-Co-V-2 viral genomes were detected and sequenced from 18 Romanian patients suffering from coronavirus disease-2019. Viral Spike S glycoprotein sequences were used to generate model structures and assess the role of mutations on protein stability. We integrated the phylogenetic tree within the available European SARS-Co-V-2 genomic sequences. We further provide an epidemiological overview of the pre-existing conditions that are lethal in relevant Romanian patients. Non-synonymous mutations in the viral Spike glycoprotein relating to infectivity are constructed in models of protein structures. Continuing search to limit and treat SARS-CoV-2 benefit from our contribution in delineating the viral Spike glycoprotein mutations, as well as from assessment of their role on protein stability or complex formation with human receptor angiotensin-converting enzyme 2. Our results help implement and extend worldwide genomic surveillance of coronavirus disease-2019.

Whole-Genome Sequences of the Severe Acute Respiratory Syndrome Coronavirus-2 obtained from Romanian patients between March and June of 2020

The SARS-CoV-2 pandemic has been growing exponentially, affecting nearly 900 thousand people and causing enormous distress to economies and societies worldwide. A plethora of analyses based on viral sequences has already been published, in scientific journals as well as through non-peer reviewed channels, to investigate SARS-CoV-2 genetic heterogeneity and spatiotemporal dissemination. We examined full genome sequences currently available to assess the presence of sufficient information for reliable phylogenetic and phylogeographic studies in countries with the highest toll of confirmed cases. Although number of-available full-genomes is growing daily, and the full dataset contains sufficient phylogenetic information that would allow reliable inference of phylogenetic relationships, country-specific SARS-CoV-2 datasets still present severe limitations. Studies assessing within country spread or transmission clusters should be considered preliminary at best, or hypothesis generating. Hence the need for continuing concerted efforts to increase number and quality of the sequences required for robust tracing of the epidemic. Significance Statement Although genome sequences of SARS-CoV-2 are growing daily and contain sufficient phylogenetic information, country-specific data still present severe limitations and should be interpreted with caution.

A snapshot of SARS-CoV-2 genome availability up to 30th March, 2020 and its implications

Recently the first genome sequence for a Severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 isolate from Bangladesh became available. The sequencing was carried out by the Child Health Research Foundation and provided the first insight into the genetic details of the viral strain responsible for the SARS-CoV-2 infections in Bangladesh. Here we carried out a comparative study were we explored the phylogenetic relationship between the Bangladeshi isolate with other isolates from different parts of the world. Afterwards we identified single nucleotide variants in the Bangladeshi isolate, using the Wuhan virus reference sequence. We found a total of 9 variants in the Bangladeshi isolate using 2 separate tools. Barring 2, the rest of these variants were also observed in other isolates from different countries. Most of the variants occurred in the ORF1ab gen. Another noteworthy finding was a sequence of three consecutive variants in the N protein gene that were observed in other isolates as well. Lastly the phylogenetic analysis revealed a close relationship between the Bangladeshi isolate and those from Taiwan, Kazakhstan, Greece, California, Spain, Israel, and Sri Lanka.

Genome Analysis of SARS-CoV-2 Isolate from Bangladesh

The COVID-19 pandemic spread very fast around the world. A few days after the first detected case in South Africa, an infection started a large hospital outbreak in Durban, KwaZulu-Natal. Phylogenetic analysis of SARS-CoV-2 genomes can be used to trace the path of transmission within a hospital. It can also identify the source of the outbreak and provide lessons to improve infection prevention and control strategies. In this manuscript, we outline the obstacles we encountered in order to genotype SARS-CoV-2 in real-time during an urgent outbreak investigation. In this process, we encountered problems with the length of the original genotyping protocol, reagent stockout and sample degradation and storage. However, we managed to set up three different library preparation methods for sequencing in Illumina. We also managed to decrease the hands on library preparation time from twelve to three hours, which allowed us to complete the outbreak investigation in just a few weeks. We also fine-tuned a simple bioinformatics workflow for the assembly of high-quality genomes in real-time. In order to allow other laboratories to learn from our experience, we released all of the library preparation and bioinformatics protocols publicly and distributed them to other laboratories of the South African Network for Genomics Surveillance (SANGS) consortium.

Whole Genome Sequencing of SARS-CoV-2: Adapting Illumina Protocols for Quick and Accurate Outbreak Investigation During a Pandemic

BACKGROUND & OBJECTIVES: Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally affected 195 countries. In India, suspected cases were screened for SARS-CoV-2 as per the advisory of the Ministry of Health and Family Welfare. The objective of this study was to characterize SARS-CoV-2 sequences from three identified positive cases as on February 29, 2020. METHODS: Throat swab/nasal swab specimens for a total of 881 suspected cases were screened by E gene and confirmed by RdRp (1), RdRp (2) and N gene real-time reverse transcription-polymerase chain reactions and next-generation sequencing. Phylogenetic analysis, molecular characterization and prediction of B- and T-cell epitopes for Indian SARS-CoV-2 sequences were undertaken. RESULTS: Three cases with a travel history from Wuhan, China, were confirmed positive for SARS-CoV-2. Almost complete (29,851 nucleotides) genomes of case 1, case 3 and a fragmented genome for case 2 were obtained. The sequences of Indian SARS-CoV-2 though not identical showed high (~99.98%) identity with Wuhan seafood market pneumonia virus (accession number: NC 045512). Phylogenetic analysis showed that the Indian sequences belonged to different clusters. Predicted linear B-cell epitopes were found to be concentrated in the S1 domain of spike protein, and a conformational epitope was identified in the receptor-binding domain. The predicted T-cell epitopes showed broad human leucocyte antigen allele coverage of A and B supertypes predominant in the Indian population. INTERPRETATION & CONCLUSIONS: The two SARS-CoV-2 sequences obtained from India represent two different introductions into the country. The genetic heterogeneity is as noted globally. The identified B- and T-cell epitopes may be considered suitable for future experiments towards the design of vaccines and diagnostics. Continuous monitoring and analysis of the sequences of new cases from India and the other affected countries would be vital to understand the genetic evolution and rates of substitution of the SARS-CoV-2.

Full-genome sequences of the first two SARS-CoV-2 viruses from India

Background & objectives: Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally affected 195 countries. In India, suspected cases were screened for SARS-CoV-2 as per the advisory of the Ministry of Health and Family Welfare. The objective of this study was to characterize SARS-CoV-2 sequences from three identified positive cases as on February 29, 2020. Methods: Throat swab/nasal swab specimens for a total of 881 suspected cases were screened by E gene and confirmed by RdRp (1), RdRp (2) and N gene real-time reverse transcription-polymerase chain reactions and next-generation sequencing. Phylogenetic analysis, molecular characterization and prediction of B- and T-cell epitopes for Indian SARS-CoV-2 sequences were undertaken. Results: Three cases with a travel history from Wuhan, China, were confirmed positive for SARS-CoV-2. Almost complete (29,851 nucleotides) genomes of case 1, case 3 and a fragmented genome for case 2 were obtained. The sequences of Indian SARS-CoV-2 though not identical showed high (~99.98%) identity with Wuhan seafood market pneumonia virus (accession number: NC 045512). Phylogenetic analysis showed that the Indian sequences belonged to different clusters. Predicted linear B-cell epitopes were found to be concentrated in the S1 domain of spike protein, and a conformational epitope was identified in the receptor-binding domain. The predicted T-cell epitopes showed broad human leucocyte antigen allele coverage of A and B supertypes predominant in the Indian population. Interpretation & conclusions: The two SARS-CoV-2 sequences obtained from India represent two different introductions into the country. The genetic heterogeneity is as noted globally. The identified B- and T-cell epitopes may be considered suitable for future experiments towards the design of vaccines and diagnostics. Continuous monitoring and analysis of the sequences of new cases from India and the other affected countries would be vital to understand the genetic evolution and rates of substitution of the SARS-CoV-2.

Different tree-building methods consistently place the SARS corona-virus (SARS-CoV) as a basal Group 2 coronavirus rather than as an ungrouped species as concluded by others. Detailed comparisons of the SARS-CoV genomic sequence with those of six other coronaviruses failed to find evidence of recombination or genomic rearrangement using computational methods designed for that purpose.

The phylogeny of SARS coronavirus

Coronaviruses are responsible on respiratory diseases in animal and human. The combination of numerical encoding techniques and digital signal processing methods are becoming increasingly important in handling large genomic data. In this paper, we propose to analyze the SARS-CoV-2 genomic signature using the combination of different nucleotide representations and signal processing tools in the aim to identify its genetic origin. The sequence of SARS-CoV-2 was compared with 21 relevant sequences including bat, yak and pangolin coronavirus sequences. In addition, we developed a new algorithm to locate the nucleotide modifications. The results show that the Bat and Pangolin coronaviruses were the most related to SARS-CoV-2 with 96% and 86% of identity all along the genome. Within the S gene sequence, the Pangolin sequence presents local highest nucleotide identity. Those findings suggest genesis of SARS-Cov-2 through evolution from bat and pangolin strains. This study offers new ways to automatically characterize viruses.

Comparative genomic signature representations of the emerging COVID-19 coronavirus and other coronaviruses: High identity and possible recombination between Bat and Pangolin coronaviruses

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been growing exponentially, affecting over 4 million people and causing enormous distress to economies and societies worldwide. A plethora of analyses based on viral sequences has already been published both in scientific journals and through non–peer-reviewed channels to investigate the genetic heterogeneity and spatiotemporal dissemination of SARS-CoV-2. However, a systematic investigation of phylogenetic information and sampling bias in the available data is lacking. Although the number of available genome sequences of SARS-CoV-2 is growing daily and the sequences show increasing phylogenetic information, country-specific data still present severe limitations and should be interpreted with caution. OBJECTIVE: The objective of this study was to determine the quality of the currently available SARS-CoV-2 full genome data in terms of sampling bias as well as phylogenetic and temporal signals to inform and guide the scientific community. METHODS: We used maximum likelihood–based methods to assess the presence of sufficient information for robust phylogenetic and phylogeographic studies in several SARS-CoV-2 sequence alignments assembled from GISAID (Global Initiative on Sharing All Influenza Data) data released between March and April 2020. RESULTS: Although the number of high-quality full genomes is growing daily, and sequence data released in April 2020 contain sufficient phylogenetic information to allow reliable inference of phylogenetic relationships, country-specific SARS-CoV-2 data sets still present severe limitations. CONCLUSIONS: At the present time, studies assessing within-country spread or transmission clusters should be considered preliminary or hypothesis-generating at best. Hence, current reports should be interpreted with caution, and concerted efforts should continue to increase the number and quality of sequences required for robust tracing of the epidemic.

The novel coronavirus (CoV), severe acute respiratory syndrome (SARS)-CoV-2 is an international public health emergency. Until now, the intermediate host and mechanisms of the interspecies jump of this virus are unknown. Phylogenetic analysis of all available bat CoV complete genomes was performed to analyze the relationships between bat CoV and SARS-CoV-2. To suggest a possible intermediate host, another phylogenetic reconstruction of CoV genomes obtained from animals that were hypothetically commercialized in the Chinese markets was also carried out. Moreover, mutation analysis was executed to suggest genomic regions that may have permitted the adaptation of SARS-CoV-2 to the human host. The phylogenetic analysis demonstrated that SARS-CoV-2 formed a cluster with the bat CoV isolate RaTG13. Possible CoV interspecies jumps among bat isolates were also observed. The phylogenetic tree reconstructed from CoV strains belonging to different animals demonstrated that SARS-CoV-2, bat RaTG13, and pangolin CoV genomes formed a monophyletic cluster, demonstrating that pangolins may be suggested as SARS-CoV-2 intermediate hosts. Three AA substitutions localized in the S1 portion of the S gene were observed, some of which have been correlated to structural modifications of the S protein which may facilitate SARS-CoV-2 tropism to human cells. Our analysis shows the tight relationship between SARS-CoV-2 and bat SARS-like strains. It also hypothesizes that pangolins might have been possible intermediate hosts of the infection. Some of the observed AA substitutions in the S-binding protein may serve as possible adaptation mutations in humans but more studies are needed to elucidate their function.

The novel coronavirus SARS-CoV-2: From a zoonotic infection to coronavirus disease 2019

BACKGROUND The aim of the current study was to investigate and track the SARS-CoV-2 in Iranian Coronavirus Disease 2019 (COVID-19) patients using molecular and phylogenetic methods. METHODS We enrolled seven confirmed cases of COVID-19 patients for the phylogenetic assessment of the SARS-CoV-2 in Iran. The nsp-2, nsp-12, and S genes were amplified using one-step RT-PCR and sequenced using Sanger sequencing method. Popular bioinformatics software were used for sequences alignment and analysis as well as phylogenetic construction. RESULTS The mean age of the patients in the present study was 60.42 ± 9.94 years and 57.1% (4/7) were male. The results indicated high similarity between Iranian and Chinese strains. We could not find any particular polymorphisms in the assessed regions of the three genes. Phylogenetic trees by neighbor-joining and maximum likelihood method of nsp-2, nsp-12, and S genes showed that there are not any differences between Iranian isolates and those of other countries. CONCLUSION As a preliminary phylogenetic study in Iranian SARS-CoV-2 isolates, we found that these isolates are closely related to the Chinese and reference sequences. Also, no sensible differences were observed between Iranian isolates and those of other countries. Further investigations are recommended using more comprehensive methods and larger sample sizes.

SARS-CoV-2 molecular and phylogenetic analysis in COVID-19 patients: A preliminary report from Iran.

BACKGROUND: The aim of the current study was to investigate and track the SARS-CoV-2 in Iranian Coronavirus Disease 2019 (COVID-19) patients using molecular and phylogenetic methods. METHODS: We enrolled seven confirmed cases of COVID-19 patients for the phylogenetic assessment of the SARS-CoV-2 in Iran. The nsp-2, nsp-12, and S genes were amplified using one-step RT-PCR and sequenced using Sanger sequencing method. Popular bioinformatics software were used for sequences alignment and analysis as well as phylogenetic construction. RESULTS: The mean age of the patients in the present study was 60.42 ± 9.94 years and 57.1% (4/7) were male. The results indicated high similarity between Iranian and Chinese strains. We could not find any particular polymorphisms in the assessed regions of the three genes. Phylogenetic trees by neighbor-joining and maximum likelihood method of nsp-2, nsp-12, and S genes showed that there are not any differences between Iranian isolates and those of other countries. CONCLUSION: As a preliminary phylogenetic study in Iranian SARS-CoV-2 isolates, we found that these isolates are closely related to the Chinese and reference sequences. Also, no sensible differences were observed between Iranian isolates and those of other countries. Further investigations are recommended using more comprehensive methods and larger sample sizes.

SARS-CoV-2 Molecular and Phylogenetic analysis in COVID-19 patients: A preliminary report from Iran

Objective: To obtain the genome sequences of SARS-CoV-2 in respiratory specimens in Guangdong Province with next-generation sequencing (NGS) and analyze the factors influencing sequencing. Methods: Eight upper and lower respiratory tract specimens were collected from patients with SARS-CoV-2 infection in Guangdong Province in January 2020. RNA library construction was used to obtain the genome sequences of SARS-CoV-2. A bio-informatics software package (CLC Genomics Workbench 12.0) was used to analyze and compare the genomic sequences. Results: Five SARS-CoV-2 genome sequences were obtained from the eight specimens and two were obtained from lower respiratory tract specimens. The nucleotide homology to SARS-CoV-2 was 97.74%-99.90%. The Ct values were lower, while the sequencing depth, coverage, relative abundance and genome integrity were higher in sequencing the SARS-CoV-2 in lower respiratory tract specimens. Conclusions: The low Ct value of SARS-CoV-2 in the samples was good for sequencing.

Whole genome sequencing of SARS-CoV-2 isolated in Guangdong Province and factors influencing the sequencing/ 广东省新型冠状病毒全基因组序列测定及其影响因素分析

OBJECTIVE: Severe acute respiratory syndrome (SARS) is caused by a new coronavirus. Genomic sequence analysis will provide the molecular epidemiology and help to develop vaccines. METHODS: We developed a rapid method to amplify and sequence the whole SARS-CoV genome from clinical specimens. The technique employed one-step multiplex RT-PCR to amplify the whole SARS-CoV genome, and then nested PCR was performed to amplify a 2-kb region separately. The PCR products were sequenced. RESULTS: We sequenced the genomes of SARS-CoV from 3 clinical specimens obtained in Taiwan. The sequences were similar to those reported by other groups, except that 17 single nucleotide variations and two 2-nucleotide deletions, and a 1-nucleotide deletion were found. All the variations in the clinical specimens did not alter the amino acid sequence. Of these 17 sequenced variants, two loci (positions 26203 and 27812) were segregated together as a specific genotype-T:T or C:C. Phylogenetic analysis showed two major clusters of SARS patients in Taiwan. CONCLUSION: We developed a very economical and rapid method to sequence the whole genome of SARS-CoV, which can avoid cultural influence. From our results, SARS patients in Taiwan may be infected from two different origins.

SARS-CoV Infection Was from at Least Two Origins in the Taiwan Area

Reply to Sánchez-Pacheco et al., Chookajorn, and Mavian et al.: Explaining phylogenetic network analysis of SARS-CoV-2 genomes

Abstract Coronaviruses are responsible on respiratory diseases in animal and human. The combination of numerical encoding techniques and digital signal processing methods are becoming increasingly important in handling large genomic data. In this paper, we propose to analyze the SARS-CoV-2 genomic signature using the combination of different nucleotide representations and signal processing tools in the aim to identify its genetic origin. The sequence of SARS-CoV-2 was compared with 21 relevant sequences including bat, yak and pangolin coronavirus sequences. In addition, we developed a new algorithm to locate the nucleotide modifications. The results show that the Bat and Pangolin coronaviruses were the most related to SARS-CoV-2 with 96% and 86% of identity all along the genome. Within the S gene sequence, the Pangolin sequence presents local highest nucleotide identity. Those findings suggest genesis of SARS-Cov-2 through evolution from bat and pangolin strains. This study offers new ways to automatically characterize viruses.

The wave of COVID-19 is a big threat to the human population. Presently, the world is going through different phases of lock down in order to stop this wave of pandemic; India being no exception. We have also started the lock down on 23rd March 2020. In this current situation, apart from social distancing only a vaccine can be the proper solution to serve the population of human being. Thus it is important for all the nations to perform the genome-wide analysis in order to identify the genetic variation in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) so that proper vaccine can be designed. This fast motivated us to analyze publicly available 566 Indian complete or near complete SARS-CoV-2 genomes to find the mutation points as substitution, deletion and insertion. In this regard, we have performed the multiple sequence alignment in presence of reference sequence from NCBI. After the alignment, a consensus sequence is build to analyze each genome in order to identify the mutation points. As a consequence, we have found 933 substitutions, 2449 deletions and 2 insertions, in total 3384 unique mutation points, in 566 genomes across 29.9 K bp. Further, it has been classified into three groups as 100 clusters of mutations (mostly deletions), 1609 point mutations as substitution, deletion and insertion and 64 SNPs. These outcomes are visualized using BioCircos and bar plots as well as plotting entropy value of each genomic location. Moreover, phylogenetic analysis has also been performed to see the evolution of SARS-CoV-2 virus in India. It also shows the wide variation in tree which indeed vivid in genomic analysis. Finally, these SNPs can be the useful target for virus classification, designing and defining the effective dose of vaccine for the heterogeneous population.

Genome-wide analysis of Indian SARS-CoV-2 genomes for the identification of genetic mutation and SNP

In December 2019, a novel human-infecting coronavirus (SARS-CoV-2) was recognized in China. In a few months, SARS-CoV-2 has caused thousands of disease cases and deaths in several countries. Phylogenetic analyses indicated that SARS-CoV-2 clusters with SARS-CoV in the Sarbecovirus subgenus and viruses related to SARS-CoV-2 were identified from bats and pangolins. Coronaviruses have long and complex genomes with high plasticity in terms of gene content. To date, the coding potential of SARS-CoV-2 remains partially unknown. We thus used available sequences of bat and pangolin viruses to determine the selective events that shaped the genome structure of SARS-CoV-2 and to assess its coding potential. By searching for signals of significantly reduced variability at synonymous sites (dS), we identified six genomic regions, one of these corresponding to the programmed -1 ribosomal frameshift. The most prominent signal of dS reduction was observed within the E gene. A genome-wide analysis of conserved RNA structures indicated that this region harbors a putative functional RNA element that is shared with the SARS-CoV lineage. Additional signals of reduced dS indicated the presence of internal ORFs. Whereas the presence ORF9a (internal to N) was previously proposed by homology with a well characterized protein of SARS-CoV, ORF3h (for hypothetical, within ORF3a) was not previously described. The predicted product of ORF3h has 90% identity with the corresponding predicted product of SARS-CoV and displays features suggestive of a viroporin. Finally, analysis of the putative ORF10 revealed high dN/dS (3.82) in SARS-CoV-2 and related coronaviruses. In the SARS-CoV lineage, the ORF is predicted to encode a truncated protein and is neutrally evolving. These data suggest that ORF10 encodes a functional protein in SARS-CoV-2 and that positive selection is driving its evolution. Experimental analyses will be necessary to validate and characterize the coding and non-coding functional elements we identified.

Coding potential and sequence conservation of SARS-CoV-2 and related animal viruses

This manuscript is based on the method we developed urgently to deal with the research requirement in the conflict between achieving a complete genome sequence for the evolutionary history of SARS-CoV-2 study and the low viral RNA concentration. Here, in this manuscript, we developed a set of SARS-CoV-2 enrichment probes to increase the sensitivity of sequence-based virus detection and characterization via obtaining the comprehensive genome sequence. Following the CDC health and safety guidelines, we test the concept using the culturing supernatant contain SARS-CoV-2 particles, and its full-length sequence was used for further analysis. The fraction of SARS-CoV-2 endogenous DNA was 93.47% with Cluster Factor about 1.1, which demonstrate that the numbers of mapped reads to SARS-CoV-2 reference sequence significantly increased, compared to metagenomic sequencing technology, following SARS-CoV-2 probe enrichment. Moreover, based on the high-quality sequence, we discussed the heterozygosity and viral expression during replication of coronavirus, and its phylogenetic relationship with other selected high-quality samples from The Genome Variation Map (GVM) (on 2020/03/22). We believe this manuscript is valuable for all the researchers who are interested in using clinical warp samples to obtain the high coverage of SARS-CoV-2 genome sequence with a relatively low concentration of viral particles. This would allow the clinician to correlate the diagnostic data with molecular monitoring in viral evolutional, the most importantly, to track the functional mutation of SARS-CoV-2.

A High-Coverage SARS-CoV-2 Genome Sequence Acquired by Target Capture Sequencing

The coronavirus disease (COVID-19) belongs to the family Severe Acute Respiratory Syndrome (SARS-CoV). It can be more severe for some persons and can lead to pneumonia or breathing difficulties resulting in the death of immune-compromised patients. We performed a phylogenomic and phylogeographic tree from the collected datasets. Phylogenomic analysis or sequence-based phylogeny showed an evolutionary relationship between the geographical strains. The phylogenomic tree grouped into two major clades consists of various isolates of SARS-CoV-2 and Bat SARS-like coronavirus, Bat coronavirus, and Pangolin coronavirus. The phylogenetic neighbor of newly sequenced Indian strains (Accession: MT012098.1, MT050493.1) was revealed to identify the variations between the nCoV-19 strains. The results showed keen evidence that SARS-CoV-2 has evolved from Bat SARS-like coronavirus. The evolutionary history and comparative proteomic analysis provide a new avenue for the current scientific research related to the coronavirus.

Phylogenomic proximity and comparative proteomic analysis of SARS-CoV-2

A pandemic caused by the SARS-CoV2 is being experienced by the whole world since December, 2019. A thorough understanding beyond just sequential similarities among the protein coding genes of SARS-CoV2 is important in order to differentiate or relate to the other known CoVs of the same genus. In this study, we compare three genomes namely MT012098 (India-Kerala), MT050493 (India-Kerala), MT358637 (India-Gujrat) from India with NC_045512 (China-Wuhan) to view the spatial as well as molecular arrangements of nucleotide bases of all the genes embedded in these four genomes. Based on different features extracted for each gene embedded in these genomes, corresponding phylogenetic relationships have been built up. Differences in phylogenetic tree arrangement with individual gene suggest that three genomes of Indian origin have come from three different origins or the evolution of viral genome is very fast process. This study would also help to understand the virulence factors, disease pathogenicity, origin and transmission of the SARS-CoV2.

On spatial molecular arrangements of SARS-CoV2 genomes of Indian patients

BACKGROUND: SARS-CoV-2 is a new coronavirus that has spread globally, infecting more than 150000 people, and being declared pandemic by the WHO. We provide here bio-informatic, evolutionary analysis of 351 available sequences of its genome with the aim of mapping genome structural variations and the patterns of selection. METHODS: A Maximum likelihood tree has been built and selective pressure has been investigated in order to find any mutation developed during the SARS-CoV-2 epidemic that could potentially affect clinical evolution of the infection. FINDING: We have found in more recent isolates the presence of two mutations affecting the Non-Structural Protein 6 (NSP6) and the Open Reding Frame10 (ORF 10) adjacent regions. Amino acidic change stability analysis suggests both mutations could confer lower stability of the protein structures. INTERPRETATION: One of the two mutations, likely developed within the genome during virus spread, could affect virus intracellular survival. Genome follow-up of SARS-CoV-2 spread is urgently needed in order to identify mutations that could significantly modify virus pathogenicity.

Evolutionary analysis of SARS-CoV-2: how mutation of Non-Structural Protein 6 (NSP6) could affect viral autophagy

The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), was declared on March 11, 2020 by the World Health Organization. As of the 31st of May, 2020, there have been more than 6 million COVID-19 cases diagnosed worldwide and over 370,000 deaths, according to Johns Hopkins. Thousands of SARS-CoV-2 strains have been sequenced to date, providing a valuable opportunity to investigate the evolution of the virus on a global scale. We performed a phylogenetic analysis of over 1,225 SARS-CoV-2 genomes spanning from late December 2019 to mid-March 2020. We identified a missense mutation, D614G, in the spike protein of SARS-CoV-2, which has emerged as a predominant clade in Europe (954 of 1,449 (66%) sequences) and is spreading worldwide (1,237 of 2,795 (44%) sequences). Molecular dating analysis estimated the emergence of this clade around mid-to-late January (10 - 25 January) 2020. We also applied structural bioinformatics to assess D614G potential impact on the virulence and epidemiology of SARS-CoV-2. In silico analyses on the spike protein structure suggests that the mutation is most likely neutral to protein function as it relates to its interaction with the human ACE2 receptor. The lack of clinical metadata available prevented our investigation of association between viral clade and disease severity phenotype. Future work that can leverage clinical outcome data with both viral and human genomic diversity is needed to monitor the pandemic.

Evolutionary and structural analyses of SARS-CoV-2 D614G spike protein mutation now documented worldwide

Four signature groups of single-nucleotide variants (SNVs) were identified using two-way clustering method in about twenty thousand high quality and high coverage SARS-CoV-2 complete genome sequences. Some frequently occurred SNVs predominate but are mutually exclusively presented in patients from different countries and areas. These major SNV signatures exhibited distinguished evolution patterns overtime. Although it was rare, our data indicated possible cross-infections with multiple groups of SNVs existed simultaneously in some patients, suggesting infections from different SARS-CoV-2 clades or potential re-combination of SARS-CoV-2 sequences. Interestingly nucleotide substitutions among SARS-CoV-2 genomes tend to occur at the sites where one bat RaTG13 coronavirus sequences differ from Wuhan-Hu-1 genome, indicating the tolerance of mutations on those sites or suggesting that major viral strains might exist between Wuhan-Hu-1 and RaTG13 coronavirus.

Distinct genetic spectrums and evolution patterns of SARS-CoV-2

Covid-19 infection, which spread to the whole world in December 2019 and is still active, caused more than 250 thousand deaths in the world today. Researches on this subject have been focused on analyzing the genetic structure of the virus, developing vaccines, the course of the disease, and its source. In this study, RNA sequences belonging to the SARS-CoV-2 virus are transformed into gene motifs with two basic image processing algorithms and classified with the convolutional neural network (CNN) models. The CNN models achieved an average of 98% Area Under Curve(AUC) value was achieved in RNA sequences classified as Asia, Europe, America, and Oceania. The resulting artificial neural network model was used for phylogenetic analysis of the variant of the virus isolated in Turkey. The classification results reached were compared with gene alignment values in the GISAID database, where SARS-CoV-2 virus records are kept all over the world. Our experimental results have revealed that now the detection of the geographic distribution of the virus with the CNN models might serve as an efficient method.

SARS-CoV-2 virus RNA sequence classification and geographical analysis with convolutional neural networks approach

Abstract As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to disperse globally with worrisome speed, identifying amino acid variations in the virus could help to understand the characteristics of it. Here, we studied 489 SARS-CoV-2 genomes obtained from 32 countries from the Nextstrain database and performed phylogenetic tree analysis by clade, country, and genotype of the surface spike glycoprotein (S protein) at site 614. We found that virus strains from mainland China were mostly distributed in Clade B and Clade undefined in the phylogenetic tree, with very few found in Clade A. In contrast, Clades A2 (one case) and A2a (112 cases) predominantly contained strains from European regions. Moreover, Clades A2 and A2a differed significantly from those of mainland China in age of infected population (P = 0.0071, mean age 40.24 to 46.66), although such differences did not exist between the US and mainland China. Further analysis demonstrated that the variation of the S protein at site 614 (QHD43416.1: p.614D>G) was a characteristic of stains in Clades A2 and A2a. Importantly, this variation was predicted to have neutral or benign effects on the function of the S protein. In addition, global quality estimates and 3D protein structures tended to be different between the two S proteins. In summary, we identified different genomic epidemiology among SARS-CoV-2 strains in different clades, especially in an amino acid variation of the S protein at 614, revealing potential viral genome divergence in SARS-CoV-2 strains.

Amino acid variation analysis of surface spike glycoprotein at 614 in SARS-CoV-2 strains

The newly identified SARS-CoV-2 has now been reported from around 183 countries with more than a million confirmed human cases including more than 68000 deaths. The genomes of SARS-COV-2 strains isolated from different parts of the world are now available and the unique features of constituent genes and proteins have gotten substantial attention recently. Spike glycoprotein is widely considered as a possible target to be explored because of its role during the entry of coronaviruses into host cells. We analyzed 320 whole-genome sequences and 320 spike protein sequences of SARS-CoV-2 using multiple sequence alignment tools. In this study, 483 unique variations have been identified among the genomes including 25 non-synonymous mutations and one deletion in the spike protein of SARS-CoV-2. Among the 26 variations detected, 12 variations were located at the N-terminal domain and 6 variations at the receptor-binding domain (RBD) which might alter the interaction with receptor molecules. In addition, 22 amino acid insertions were identified in the spike protein of SARS-CoV-2 in comparison with that of SARS-CoV. Phylogenetic analyses of spike protein revealed that Bat coronavirus have a close evolutionary relationship with circulating SARS-CoV-2. The genetic variation analysis data presented in this study can help a better understanding of SARS-CoV-2 pathogenesis. Based on our findings, potential inhibitors can be designed and tested targeting these proposed sites of variation.

Exploring the genomic and proteomic variations of SARS-CoV-2 spike glycoprotein: a computational biology approach

COVID-A9 is an infection disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), declared as a pandemic due to its rapid expansion worldwide. In this study we investigate the genetic diversity and genomic epidemiology of SARS-CoV-2 using 22 virus genome sequences reported by three different laboratories in Morocco till the date 07/06/2020 as well as (40366) virus genomes from all around the world. The SARS-CoV-2 genomes from Moroccan patients revealed 62 mutations of which 30 were missense mutations. The mutations Spike_D614G and NSP12_P323L were present in all the 22 analyzed sequences, followed by N_G204R and N_R203K which occurred in 9 among the 22 sequences. The mutations NSP10_R134S, NSP15_D335N, NSP16_I169L, NSP3_L431H, NSP3_P1292L and Spike_V6F occurred one time in our sequences with no record in other sequence worldwide. These mutations should be investigated to figure out their potential effects on all around the world virulence. Phylogenetic analyses revealed that Moroccan SARS-CoV-2 genomes included 9 viruses pertaining to clade 20A, 9 to clade 20B and 2 to clade 20C. This finding suggest that the epidemic spread in Morocco did not show a predominant SARS-CoV-2 route. For multiple and unrelated introductions of SARS-CoV-2 into Morocco via different routes have occurred, giving rise to the diversity of virus genomes in the country. Furthermore, very likely, the SARS-CoV-2 virus circulated in cryptic way in Morocco starting from the fifteen January before the discovering of the first case the second of March.

Genetic Diversity and Genomic Epidemiology of SARS-COV-2 in Morocco

The novel coronavirus SARS-CoV-2 (2019-nCoV) is a member of the family coronaviridae and contains a single-stranded RNA genome with positive-polarity. To reveal the evolution mechanism of SARS-CoV-2 genome, we performed comprehensive genomic analysis with newly sequenced SARS-CoV-2 strains and 20 closely related coronavirus strains. Among 98 nucleotide mutations at 93 sites of the genome among different SARS-CoV-2 strains, 58 of them caused amino acid change, indicating a result of neutral evolution. However, the ratio of nucleotide substitutions to amino acid substitutions of spike gene (9.07) between SARS-CoV-2 WIV04 and Bat-SARSr-CoV RaTG13 was extensively higher than those from comparisons between other coronaviruses (range 1.29 - 4.81). The elevated synonymous mutations between SARS-CoV-2 and RaTG13, suggesting they underwent stronger purifying selection. Moreover, their nucleotide substitutions are enriched with T:C transition, which is consistent with the mutation signature caused by deactivity of RNA 3’-to-5’ exoribonuclease (ExoN). The codon usage was similar between SARS-CoV-2 and other strains in beta-coronavirus lineage B, suggesting it had small impact on the mutation pattern. In comparison of SARS-CoV-2 WIV04 with Bat-SARSr-CoV RaTG13, the ratios of non-synonymous to synonymous substitution rates (dN/dS) was the lowest among all performed comparisons, reconfirming the evolution of SARS-CoV-2 under stringent selective pressure. Moreover, some sites of spike protein might be subjected to positive selection. Therefore, our results will help understanding the evolutionary mechanisms contribute to viral pathogenicity and its adaptation with hosts.

Comparative genomic analysis revealed specific mutation pattern between human coronavirus SARS-CoV-2 and Bat-SARSr-CoV RaTG13

Abstract Background SARS-CoV-2 is a new coronavirus that has spread globally, infecting more than 150000 people, and being declared pandemic by the WHO. We provide here bio-informatic, evolutionary analysis of 351 available sequences of its genome with the aim of mapping genome structural variations and the patterns of selection. Methods A Maximum likelihood tree has been built and selective pressure has been investigated in order to find any mutation developed during the SARS-CoV-2 epidemic that could potentially affect clinical evolution of the infection. Finding We have found in more recent isolates the presence of two mutations affecting the Non-Structural Protein 6 (NSP6) and the Open Reding Frame10 (ORF 10) adjacent regions. Amino acidic change stability analysis suggests both mutations could confer lower stability of the protein structures. Interpretation One of the two mutations, likely developed within the genome during virus spread, could affect virus intracellular survival. Genome follow-up of SARS-CoV-2 spread is urgently needed in order to identify mutations that could significantly modify virus pathogenicity.

The origin of the severe acute respiratory syndrome‐coronavirus (SARS‐CoV) remains unclear. Evidence based on Bayesian scanning plots and phylogenetic analysis using maximum likelihood (ML) and Bayesian methods indicates that SARS‐CoV, for the largest part of the genome (∼80%), is more closely related to Group II coronaviruses sequences, whereas in three regions in the ORF1ab gene it shows no apparent similarity to any of the previously characterized groups of coronaviruses. There is discordant phylogenetic clustering of SARS‐CoV and coronaviruses sequences, throughout the genome, compatible with either ancient recombination events or altered evolutionary rates in different lineages, or a combination of both. J. Med. Virol. 74:369–372, 2004. © 2004 Wiley‐Liss, Inc.

Phylogenetic analysis of the full‐length SARS‐CoV sequences: Evidence for phylogenetic discordance in three genomic regions

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10-3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

Abstract A new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) associated with human to human transmission and extreme human sickness has been as of late announced from the city of Wuhan in China. Our objectives were to mutation analysis between recently reported genomes at various times and locations and to characterize the genomic structure of SARS-CoV-2 using bioinformatics programs. Information on the variation of viruses is of considerable medical and biological impacts on the prevention, diagnosis, and therapy of infectious diseases. To understand the genomic structure and variations of the SARS-CoV-2. The study analyzed 95 SARS-CoV-2 complete genome sequences available in GenBank, National MicrobiologyData Center (NMDC) and NGDC Genome Warehouse from December-2019 until 05 of April-2020. The genomic signature analysis demonstrates that a strong association between the time of sample collection, location of sample and accumulation of genetic diversity. We found 116 mutations, the three most common mutations were 8782C>T in ORF1ab gene, 28144T>C in ORF8 gene and 29095C>T in the N gene. The mutations might affect the severity and spread of the SARS-CoV-2. The finding heavily supports an intense requirement for additional prompt, inclusive investigations that combine genomic detail, epidemiological information and graph records of the clinical features of patients with COVID-19.

Genomic characterization of a novel SARS-CoV-2

The phylogenetic clustering of 95 SARS-CoV-2 sequences from the first 3 months of the pandemic reveals insights into the early evolution of the virus and gives first indications of how the variants are globally distributed. Variants might become a challenge in terms of diagnostics, immunology, and effectiveness of drugs. All available whole genome sequence data from the NCBI database (March 16, 2020) were phylogenetically analyzed, and gene prediction as well as analysis of selected variants were performed. Antigenic regions and the secondary protein structure were predicted for selected variants. While some clusters are presenting the same variant with 100% identical bases, other SARS-CoV-2 lineages show a beginning diversification and phylogenetic clustering due to base substitutions and deletions in the genomes. First molecular epidemiological investigations are possible with the results by adding metadata as travelling history to the presented data. The advantage of variants in source tracing can be a challenge in terms of virulence, immune response, and immunological memory. Variants of viruses often show differences in virulence or antigenicity. This must also be considered in decisions like herd immunity. Diagnostic methods might not work if the variations or deletions are in target regions for the detection of the pathogen. One base substitution was detected in a primer binding site.

Early Phylogenetic Diversification of SARS-CoV-2: Determination of Variants and the Effect on Epidemiology, Immunology, and Diagnostics.

The newly identified SARS-CoV-2 has now been reported from around 185 countries with more than a million confirmed human cases including more than 120,000 deaths. The genomes of SARS-COV-2 strains isolated from different parts of the world are now available and the unique features of constituent genes and proteins need to be explored to understand the biology of the virus. Spike glycoprotein is one of the major targets to be explored because of its role during the entry of coronaviruses into host cells. We analyzed 320 whole-genome sequences and 320 spike protein sequences of SARS-CoV-2 using multiple sequence alignment. In this study, 483 unique variations have been identified among the genomes of SARS-CoV-2 including 25 nonsynonymous mutations and one deletion in the spike (S) protein. Among the 26 variations detected, 12 variations were located at the N-terminal domain and 6 variations at the receptor-binding domain (RBD) which might alter the interaction of S protein with the host receptor angiotensin converting enzyme-2 (ACE2). Besides, 22 amino acid insertions were identified in the spike protein of SARS-CoV-2 in comparison with that of SARS-CoV. Phylogenetic analyses of spike protein revealed that Bat coronavirus have a close evolutionary relationship with circulating SARS-CoV-2. The genetic variation analysis data presented in this study can help a better understanding of SARS-CoV-2 pathogenesis. Based on results reported herein, potential inhibitors against S protein can be designed by considering these variations and their impact on protein structure.

Exploring the genomic and proteomic variations of SARS-CoV-2 spike glycoprotein: A computational biology approach

As the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), rages across the world, killing hundreds of thousands and infecting millions, researchers are racing against time to elucidate the viral genome. Some Bangladeshi institutes are also in this race, sequenced a few isolates of the virus collected from Bangladesh. Here, we present a genomic analysis of 14 isolates. The analysis revealed that SARS-CoV-2 isolates sequenced from Dhaka and Chittagong were the lineage of Europe and the Middle East, respectively. Our analysis identified a total of 42 mutations, including three large deletions, half of which were synonymous. Most of the missense mutations in Bangladeshi isolates found to have weak effects on the pathogenesis. Some mutations may lead the virus to be less pathogenic than the other countries. Molecular docking analysis to evaluate the effect of the mutations on the interaction between the viral spike proteins and the human ACE2 receptor, though no significant interaction was observed. This study provides some preliminary insights into the origin of Bangladeshi SARS-CoV-2 isolates, mutation spectrum and its possible pathomechanism, which may give an essential clue for designing therapeutics and management of COVID-19 in Bangladesh.

Genetic analysis of SARS-CoV-2 isolates collected from Bangladesh: insights into the origin, mutation spectrum, and possible pathomechanism

Median-joining network analysis of SARS-CoV-2 genomes is neither phylogenetic nor evolutionary

In a phylogenetic network analysis of 160 complete human severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) genomes, we find three central variants distinguished by amino acid changes, which we have named A, B, and C, with A being the ancestral type according to the bat outgroup coronavirus. The A and C types are found in significant proportions outside East Asia, that is, in Europeans and Americans. In contrast, the B type is the most common type in East Asia, and its ancestral genome appears not to have spread outside East Asia without first mutating into derived B types, pointing to founder effects or immunological or environmental resistance against this type outside Asia. The network faithfully traces routes of infections for documented coronavirus disease 2019 (COVID-19) cases, indicating that phylogenetic networks can likewise be successfully used to help trace undocumented COVID-19 infection sources, which can then be quarantined to prevent recurrent spread of the disease worldwide.

Phylogenetic network analysis of SARS-CoV-2 genomes

Starting around December 2019, an epidemic of pneumonia, which was named COVID-19 by the World Health Organization, broke out in Wuhan, China, and is spreading throughout the world. A new coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the Coronavirus Study Group of the International Committee on Taxonomy of Viruses was soon found to be the cause. At present, the sensitivity of clinical nucleic acid detection is limited, and it is still unclear whether it is related to genetic variation. In this study, we retrieved 95 full-length genomic sequences of SARAS-CoV-2 strains from the National Center for Biotechnology Information and GISAID databases, established the reference sequence by conducting multiple sequence alignment and phylogenetic analyses, and analyzed sequence variations along the SARS-CoV-2 genome. The homology among all viral strains was generally high, among them, 99.99% (99.91%-100%) at the nucleotide level and 99.99% (99.79%-100%) at the amino acid level. Although overall variation in open-reading frame (ORF) regions is low, 13 variation sites in 1a, 1b, S, 3a, M, 8, and N regions were identified, among which positions nt28144 in ORF 8 and nt8782 in ORF 1a showed mutation rate of 30.53% (29/95) and 29.47% (28/95), respectively. These findings suggested that there may be selective mutations in SARS-COV-2, and it is necessary to avoid certain regions when designing primers and probes. Establishment of the reference sequence for SARS-CoV-2 could benefit not only biological study of this virus but also diagnosis, clinical monitoring and intervention of SARS-CoV-2 infection in the future.

The establishment of reference sequence for SARS-CoV-2 and variation analysis

Abstract Background Phyloepidemiologic approaches have given specific insight to understanding emergence and evolution of infection. Knowledge on the outbreak and spread of SARS-CoV-2 in Nigeria would assist in providing preventive measures to reduce transmission among populations at risk. Therefore, this study aimed at investigating the evolution of SARS-CoV-2 in Nigeria. Materials and Method A total of 39 complete genomes of SARS-CoV-2 were retrieved from the GISAID EpiFluTM database on March 29th 2020 to investigate its evolution in Nigeria. Sequences were selected based on the travel history of the patient and the collection date. Other sequences were not selected because they were short, contained artefacts, not from original source or had insufficient information. Evolutionary history was inferred using Maximum Likelihood method based on the General Time Reversible model. Phylogenetic tree was constructed to determine the common ancestor of each strain. Results The phylogenetic analysis showed the strain in Nigeria clustered in a monophyletic clade with a Wuhan sublineage. Nucleotide alignment also showed a 100% similarity indicating a common origin of evolution. Comparative analysis showed 27,972 (93.6%) identical sites and 97.6% pairwise identity with the consensus. Conclusion The study evidently showed the entire outbreak of COVID-19 infection in Nigeria stemmed from a single introduction sharing consensus similarity with the reference SARS-CoV-2 human genome from Wuhan. Preventive measures that can limit the spread of the infection among populations at risk should be implemented.

Phyloevolutionary analysis of SARS-CoV-2 in Nigeria

The novel human coronavirus (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) pandemic worldwide. The increasing sequencing data have shown abundant single nucleotide variations in SARS-CoV-2 genome. However, it is difficult to quickly analyze genomic variation and screen key mutations of SARS-CoV-2. In this study, we developed a visual program, named BioAider, for quick and convenient sequence annotation and mutation analysis on multiple genome-sequencing data. Using BioAider, we conducted a comprehensive genome variation analysis on 3,240 sequences of SARS-CoV-2 genome. Herein, we detected 14 substitution hotspots within SARS-CoV-2 genome, including 10 non-synonymous and 4 synonymous ones. Among these hotspots, NSP13-Y541C was predicted to be a crucial substitution which might affect the unwinding activity of NSP13, a key protein for viral replication. Besides, we also found 3 groups of potentially linked substitution hotspots which were worth further study. In particular, we discovered a SR-rich region (aa 184-204) on the N protein of SARS-CoV-2 distinct from SARS-CoV, indicating more complex replication mechanism and unique N-M interaction of SARS-CoV-2. Interestingly, the quantity of SRXX repeat fragments in the SR-rich region well reflected the evolutionary relationship among SARS-CoV-2 and SARS-CoV-2 related animal coronaviruses, providing further evidence of its animal origin. Overall, we developed an efficient tool for rapid identification of mutations, identified substitution hotspots in SARS-CoV-2 genomes, and detected a distinctive polymorphism SR-rich region in N protein. This tool and the detected hotspots could facilitate the viral genomic study and may contribute for screening antiviral target sites.

Characterization of the substitution hotspots in SARS-CoV-2 genome using BioAider and detection of a SR-rich region in N protein providing further evidence of its animal origin

Research efforts of the ongoing SARS-CoV-2 pandemic have focused on viral genome sequence analysis to understand how the virus spread across the globe. Here, we assess three recently identified SARS-CoV-2 genomes in Beijing from June 2020 and attempt to determine the origin of these genomes, made available in the GISAID database. The database contains fully or partially sequenced SARS-CoV-2 samples from laboratories around the world. Including the three new samples and excluding samples with missing annotations, we analyzed 7, 643 SARS-CoV-2 genomes. Using principal component analysis computed on a similarity matrix that compares all pairs of the SARS-CoV-2 nucleotide sequences at all loci simultaneously, using the Jaccard index, we find that the newly discovered virus genomes from Beijing are in a genetic cluster that consists mostly of cases from Europe and South(east) Asia. The sequences of the new cases are most related to virus genomes from a small number of cases from China (March 2020), cases from Europe (February to early May 2020), and cases from South(east) Asia (May to June 2020). These findings could suggest that the original cases of this genetic cluster originated from China in March 2020 and were re-introduced to China by transmissions from samples from South(east) Asia between April and June 2020.

Unsupervised cluster analysis of SARS-CoV-2 genomes indicates that recent (June 2020) cases in Beijing are from a genetic subgroup that consists of mostly European and South(east) Asian samples, of which the latter are the most recent

The first Indian cases of COVID-19 caused by SARS-Cov-2 were reported in February 29, 2020 with a history of travel from Wuhan, China and so far above 4500 deaths have been attributed to this pandemic. The objectives of this study were to characterize Indian SARS-CoV-2 genome-wide nucleotide variations, trace ancestries using phylogenetic networks and correlate state-wise distribution of viral haplotypes with differences in mortality rates. A total of 305 whole genome sequences from 19 Indian states were downloaded from GISAID. Sequences were aligned using the ancestral Wuhan-Hu genome sequence (NC_045512.2). A total of 633 variants resulting in 388 amino acid substitutions were identified. Allele frequency spectrum, and nucleotide diversity (π) values revealed the presence of higher proportions of low frequency variants and negative Tajima’s D values across ORFs indicated the presence of population expansion. Network analysis highlighted the presence of two major clusters of viral haplotypes, namely, clade G with the S:D614G, RdRp: P323L variants and a variant of clade L [Lv] having the RdRp:A97V variant. Clade G genomes were found to be evolving more rapidly into multiple sub-clusters including clade GH and GR and were also found in higher proportions in three states with highest mortality rates namely, Gujarat, Madhya Pradesh and West Bengal.

Phylogenetic clustering of the Indian SARS-CoV-2 genomes reveals the presence of distinct clades of viral haplotypes among states

The sudden emergence of severe respiratory disease, caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a public health emergency. Genome sequence analysis of SARS-CoV-2 revealed its close resemblance to the earlier reported SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). However, initial testing of the drugs used against SARS-CoV and MERS-CoV has been ineffective in controlling SARS-CoV-2. The present study highlights the genomic, proteomic, pathogenesis, and therapeutic strategies in SARS-CoV-2 infection. We have carried out sequence analysis of potential drug target proteins in SARS-CoV-2 and, compared them with SARS-CoV and MERS viruses. Analysis of mutations in the coding and non-coding regions, genetic diversity, and pathogenicity of SARS-CoV-2 has also been done. A detailed structural analysis of drug target proteins has been performed to gain insights into the mechanism of pathogenesis, structure-function relationships, and the development of structure-guided therapeutic approaches. The cytokine profiling and inflammatory signalling are different in the case of SARS-CoV-2 infection. We also highlighted possible therapies and their mechanism of action followed by clinical manifestation. Our analysis suggests a minimal variation in the genome sequence of SARS-CoV-2, may be responsible for a drastic change in the structures of target proteins, which makes available drugs ineffective.

Insights into SARS-CoV-2 genome, structure, evolution, pathogenesis and therapies: Structural genomics approach

From an isolated epidemic, COVID-19 has now emerged as a global pandemic. The availability of genomes in the public domain following the epidemic provides a unique opportunity to understand the evolution and spread of the SARS-CoV-2 virus across the globe. The availability of whole genomes from multiple states in India prompted us to analyse the phylogenetic clusters of genomes in India. We performed whole-genome sequencing for 64 genomes making a total of 361 genomes from India, followed by phylogenetic clustering, substitution analysis, and dating of the different phylogenetic clusters of viral genomes. We describe a distinct phylogenetic cluster (Clade I / A3i) of SARS-CoV-2 genomes from India, which encompasses 41% of all genomes sequenced and deposited in the public domain from multiple states in India. Globally 3.5% of genomes, which till date could not be mapped to any distinct known cluster fall in this newly defined clade. The cluster is characterized by a core set of shared genetic variants – C6312A (T2016K), C13730T (A88V/A97V), C23929T, and C28311T (P13L). Further, the cluster is also characterized by a nucleotide substitution rate of 1.4 × 10−3 variants per site per year, lower than the prevalent A2a cluster, and predominantly driven by variants in the E and N genes and relative sparing of the S gene. Epidemiological assessments suggest that the common ancestor emerged in the month of February 2020 and possibly resulted in an outbreak followed by countrywide spread, as evidenced by the low divergence of the genomes from across the country. To the best of our knowledge, this is the first comprehensive study characterizing the distinct and predominant cluster of SARS-CoV-2 in India.

A distinct phylogenetic cluster of Indian SARS-CoV-2 isolates

We sequenced the 29,751-base genome of the severe acute respiratory syndrome (SARS)-associated coronavirus known as the Tor2 isolate. The genome sequence reveals that this coronavirus is only moderately related to other known coronaviruses, including two human coronaviruses, HCoV-OC43 and HCoV-229E. Phylogenetic analysis of the predicted viral proteins indicates that the virus does not closely resemble any of the three previously known groups of coronaviruses. The genome sequence will aid in the diagnosis of SARS virus infection in humans and potential animal hosts (using polymerase chain reaction and immunological tests), in the development of antivirals (including neutralizing antibodies), and in the identification of putative epitopes for vaccine development.

The Genome sequence of the SARS-associated coronavirus.

Abstract In December 2019, a novel human-infecting coronavirus (SARS-CoV-2) was recognized in China. In a few months, SARS-CoV-2 has caused thousands of disease cases and deaths in several countries. Phylogenetic analyses indicated that SARS-CoV-2 clusters with SARS-CoV in the Sarbecovirus subgenus and viruses related to SARS-CoV-2 were identified from bats and pangolins. Coronaviruses have long and complex genomes with high plasticity in terms of gene content. To date, the coding potential of SARS-CoV-2 remains partially unknown. We thus used available sequences of bat and pangolin viruses to determine the selective events that shaped the genome structure of SARS-CoV-2 and to assess its coding potential. By searching for signals of significantly reduced variability at synonymous sites (dS), we identified six genomic regions, one of these corresponding to the programmed −1 ribosomal frameshift. The most prominent signal of dS reduction was observed within the E gene. A genome-wide analysis of conserved RNA structures indicated that this region harbors a putative functional RNA element that is shared with the SARS-CoV lineage. Additional signals of reduced dS indicated the presence of internal ORFs. Whereas the presence ORF9a (internal to N) was previously proposed by homology with a well characterized protein of SARS-CoV, ORF3h (for hypothetical, within ORF3a) was not previously described. The predicted product of ORF3h has 90% identity with the corresponding predicted product of SARS-CoV and displays features suggestive of a viroporin. Finally, analysis of the putative ORF10 revealed high dN/dS (3.82) in SARS-CoV-2 and related coronaviruses. In the SARS-CoV lineage, the ORF is predicted to encode a truncated protein and is neutrally evolving. These data suggest that ORF10 encodes a functional protein in SARS-CoV-2 and that positive selection is driving its evolution. Experimental analyses will be necessary to validate and characterize the coding and non-coding functional elements we identified.

Coding potential and sequence conservation of SARS-CoV-2 and related animal viruses

The newly identified SARS-CoV-2 has now been reported from around 185 countries with more than a million confirmed human cases including more than 120,000 deaths. The genomes of SARS-COV-2 strains isolated from different parts of the world are now available and the unique features of constituent genes and proteins need to be explored to understand the biology of the virus. Spike glycoprotein is one of the major targets to be explored because of its role during the entry of coronaviruses into host cells. We analyzed 320 whole-genome sequences and 320 spike protein sequences of SARS-CoV-2 using multiple sequence alignment. In this study, 483 unique variations have been identified among the genomes of SARS-CoV-2 including 25 nonsynonymous mutations and one deletion in the spike (S) protein. Among the 26 variations detected in S, 12 variations were located at the N-terminal domain (NTD) and 6 variations at the receptor-binding domain (RBD) which might alter the interaction of S protein with the host receptor angiotensin-converting enzyme 2 (ACE2). Besides, 22 amino acid insertions were identified in the spike protein of SARS-CoV-2 in comparison with that of SARS-CoV. Phylogenetic analyses of spike protein revealed that Bat coronavirus have a close evolutionary relationship with circulating SARS-CoV-2. The genetic variation analysis data presented in this study can help a better understanding of SARS-CoV-2 pathogenesis. Based on results reported herein, potential inhibitors against S protein can be designed by considering these variations and their impact on protein structure.

OBJECTIVES: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in December 2019 and has been rapidly spreading worldwide. Although the causal relationship among mutations and the features of SARS-CoV-2 such as rapid transmission, pathogenicity, and tropism, remains unclear, our results of genomic mutations in SARS-CoV-2 may help to interpret the interaction between genomic characterization in SARS-CoV-2 and infectivity with the host. METHODS: A total of 4,254 genomic sequences of SARS-CoV-2 were collected from the Global Initiative on Sharing all Influenza Data (GISAID). Multiple sequence alignment for phylogenetic analysis and comparative genomic approach for mutation analysis were conducted using Molecular Evolutionary Genetics Analysis (MEGA), and an in-house program based on Perl language, respectively. RESULTS: Phylogenetic analysis of SARS-CoV-2 strains indicated that there were 3 major clades including S, V, and G, and 2 subclades (G.1 and G.2). There were 767 types of synonymous and 1,352 types of non-synonymous mutation. ORF1a, ORF1b, S, and N genes were detected at high frequency, whereas ORF7b and E genes exhibited low frequency. In the receptor-binding domain (RBD) of the S gene, 11 non-synonymous mutations were observed in the region adjacent to the angiotensin converting enzyme 2 (ACE2) binding site. CONCLUSION: It has been reported that the rapid infectivity and transmission of SARS-CoV-2 associated with host receptor affinity are derived from several mutations in its genes. Without these genetic mutations to enhance evolutionary adaptation, species recognition, host receptor affinity, and pathogenicity, it would not survive. It is expected that our results could provide an important clue in understanding the genomic characteristics of SARS-CoV-2.

Genome-Wide Identification and Characterization of Point Mutations in the SARS-CoV-2 Genome

AIM Recently, more SARS-CoV virus genome sequences are released to the GenBank database. The aim of this study is to reveal the evolution forces of SARS-CoV virus by analyzing the nucleotide mutations in these sequences. METHODS We obtained 20 SARS-CoV virus genome sequences from NCBI database, and calculated the ratio of non-synonymous nucleotide substitution per non-synonymous site (Ka) and synonymous nucleotide substitution per synonymous site (Ks) for SARS-CoV virus genes. RESULTS The Ka/Ks ratios for replicase polyprotein ORF1a, ORF1b, and spike protein gene are 1.09 (P=0.6501), 0.38 (P=0.0074), 0.65 (P=0.0685) respectively. CONCLUSION SARS-CoV virus replicase polyprotein ORF1b is undergoing negative selection; negative selection force is also probably operating on spike protein gene. These results provide basis for future developing a new drug and vaccine against SARS.

Mutation analysis of 20 SARS virus genome sequences: evidence for negative selection in replicase ORF1b and spike gene.

Monitoring the mutation dynamics of SARS-CoV-2 is critical for the development of effective approaches to contain the pathogen. By analyzing 106 SARS-CoV-2 and 39 SARS genome sequences, we provided direct genetic evidence that SARS-CoV-2 has a much lower mutation rate than SARS. Minimum Evolution phylogeny analysis revealed the putative original status of SARS-CoV-2 and the early-stage spread history. The discrepant phylogenies for the spike protein and its receptor binding domain proved a previously reported structural rearrangement prior to the emergence of SARS-CoV-2. Despite that we found the spike glycoprotein of SARS-CoV-2 is particularly more conserved, we identified a mutation that leads to weaker receptor binding capability, which concerns a SARS-CoV-2 sample collected on 27th January 2020 from India. This represents the first report of a significant SARS-CoV-2 mutant, and raises the alarm that the ongoing vaccine development may become futile in future epidemic if more mutations were identified. Highlights Based on the currently available genome sequence data, we proved that SARS-COV-2 genome has a much lower mutation rate and genetic diversity than SARS during the 2002-2003 outbreak. The spike (S) protein encoding gene of SARS-COV-2 is found relatively more conserved than other protein-encoding genes, which is a good indication for the ongoing antiviral drug and vaccine development. Minimum Evolution phylogeny analysis revealed the putative original status of SARS-CoV-2 and the early-stage spread history. We confirmed a previously reported rearrangement in the S protein arrangement of SARS-COV-2, and propose that this rearrangement should have occurred between human SARS-CoV and a bat SARS-CoV, at a time point much earlier before SARS-COV-2 transmission to human. We provided first evidence that a mutated SARS-COV-2 with reduced human ACE2 receptor binding affinity have emerged in India based on a sample collected on 27th January 2020.

Analysis of the mutation dynamics of SARS-CoV-2 reveals the spread history and emergence of RBD mutant with lower ACE2 binding affinity

During the past three months, a new coronavirus (SARS-CoV-2) epidemic has been growing exponentially, affecting over 100 thousand people worldwide, and causing enormous distress to economies and societies of affected countries. A plethora of analyses based on viral sequences has already been published, in scientific journals as well as through non-peer reviewed channels, to investigate SARS-CoV-2 genetic heterogeneity and spatiotemporal dissemination. We examined all full genome sequences currently available to assess the presence of sufficient information for reliable phylogenetic and phylogeographic studies. Our analysis clearly shows severe limitations in the present data, in light of which any finding should be considered, at the very best, preliminary and hypothesis-generating. Hence the need for avoiding stigmatization based on partial information, and for continuing concerted efforts to increase number and quality of the sequences required for robust tracing of the epidemic.

Regaining perspective on SARS-CoV-2 molecular tracing and its implications

The emerging global infectious COVID-19 coronavirus disease by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) presents critical threats to global public health and the economy since it was identified in late December 2019 in China. The virus has gone through various pathways of evolution. For understanding the evolution and transmission of SARS-CoV-2, genotyping of virus isolates is of great importance. We present an accurate method for effectively genotyping SARS-CoV-2 viruses using complete genomes. The method employs the multiple sequence alignments of the genome isolates with the SARS-CoV-2 reference genome. The SNP genotypes are then measured by Jaccard distances to track the relationship of virus isolates. The genotyping analysis of SARS-CoV-2 isolates from the globe reveals that specific multiple mutations are the predominated mutation type during the current epidemic. Our method serves a promising tool for monitoring and tracking the epidemic of pathogenic viruses in their gradual and local genetic variations. The genotyping analysis shows that the genes encoding the S proteins and RNA polymerase, RNA primase, and nucleoprotein, undergo frequent mutations. These mutations are critical for vaccine development in disease control.

Genotyping coronavirus SARS-CoV-2: methods and implications

Here we aim to describe early mutational events across samples from publicly available SARS-CoV-2 sequences from the sequence read archive and GenBank repositories. Up until 27 March 2020, we downloaded 50 illumina datasets, mostly from China, USA (WA State) and Australia (VIC). A total of 30 datasets (60%) contain at least a single founder mutation and most of the variants are missense (over 63%). Five-point mutations with clonal (founder) effect were found in USA next-generation sequencing samples. Sequencing samples from North America in GenBank (22 April 2020) present this signature with up to 39% allele frequencies among samples (n = 1,359). Australian variant signatures were more diverse than USA samples, but still, clonal events were found in these samples. Mutations in the helicase, encoded by the ORF1ab gene in SARS-CoV-2 were predominant, among others, suggesting that these regions are actively evolving. Finally, we firmly urge that primer sets for diagnosis be carefully designed, since rapidly occurring variants would affect the performance of the reverse transcribed quantitative PCR (RT-qPCR) based viral testing.

Insights on early mutational events in SARS-CoV-2 virus reveal founder effects across geographical regions

BACKGROUND: More than 2 months separated the initial description of SARS-CoV-2 and discovery of its widespread dissemination in the United States. Despite this lengthy interval, implementation of specific quantitative reverse transcription (qRT)-PCR-based SARS-CoV-2 tests in the US has been slow, and testing is still not widely available. Metagenomic sequencing offers the promise of unbiased detection of emerging pathogens, without requiring prior knowledge of the identity of the responsible agent or its genomic sequence. METHODS: To evaluate metagenomic approaches in the context of the current SARS-CoV-2 epidemic, laboratory-confirmed positive and negative samples from Seattle, WA were evaluated by metagenomic sequencing, with comparison to a 2019 reference genomic database created before the emergence of SARS-CoV-2. RESULTS: Within 36 h our results showed clear identification of a novel human Betacoronavirus, closely related to known Betacoronaviruses of bats, in laboratory-proven cases of SARS-CoV-2. A subset of samples also showed superinfection or colonization with human parainfluenza virus 3 or Moraxella species, highlighting the need to test directly for SARS-CoV-2 as opposed to ruling out an infection using a viral respiratory panel. Samples negative for SARS-CoV-2 by RT-PCR were also negative by metagenomic analysis, and positive for Rhinovirus A and C. Unlike targeted SARS-CoV-2 qRT-PCR testing, metagenomic analysis of these SARS-CoV-2 negative samples identified candidate etiological agents for the patients' respiratory symptoms. CONCLUSION: Taken together, these results demonstrate the value of metagenomic analysis in the monitoring and response to this and future viral pandemics.

Metagenomic Analysis Reveals Clinical SARS-CoV-2 Infection and Bacterial or Viral Superinfection and Colonization

The recent zoonotic coronavirus virus outbreak of a novel type [COVID 19] has necessitated the adequate understanding of the evolutionary pathway of zoonotic viruses which adversely affects human populations for therapeutic constructs to combat the pandemic now and in the future. We analyzed conserved domains of the severe acute respiratory coronavirus 2 [SARS-CoV2] for possible targets of viral entry inhibition in host cells, evolutionary relationship of human coronavirus [229E] and zoonotic coronaviruses with SAR-CoV2 as well as evolutionary relationship between selected SARS-CoV 2 genomic data. Conserved domains with antagonistic action on host innate antiviral cellular mechanisms in SARS-CoV 2 include nsp 11, nsp 13 etc. Also, multiple sequence alignments of the spike [S] gene protein of selected candidate zoonotic coronaviruses alongside the S gene protein of the SARs-CoV2 revealed closest evolutionary relationship [95.6%] with pangolin coronaviruses [S] gene. Clades formed between Wuhan SARS-CoV2 phylogeny data and five others suggests viral entry trajectory while revealing genomic and protein SARS CoV 2 data from Philippines as early ancestors. Therefore, phylogeny of SARS-CoV 2 genomic data suggests profiling in diverse populations with and without the outbreak alongside migration history and racial background for mutation tracking and dating of viral subtype divergence which is essential for effective management of present and future zoonotic coronavirus outbreaks.

In-silico nucleotide and protein analyses of S-gene region in selected zoonotic coronaviruses reveal conserved domains and evolutionary emergence with trajectory course of viral entry from SARS-CoV2 genomic data

Objectives To reveal epidemic trend and possible origins of SARS-CoV-2 by exploring its evolution and molecular characteristics based on a large number of genomes since it has infected millions of people and spread quickly all over the world. Methods Various evolution analysis methods were employed. Results The estimated Ka/Ks ratio of SARS-CoV-2 is 1.008 or 1.094 based on 622 or 3624 SARS-CoV-2 genomes, and the time to the most recent common ancestor (tMRCA) was inferred in late September 2019. Further 9 key specific sites of highly linkage and four major haplotypes H1, H2, H3 and H4 were found. The Ka/Ks, detected population size and development trends of each major haplotype showed H3 and H4 subgroups were going through a purify evolution and almost disappeared after detection, indicating H3 and H4 might have existed for a long time, while H1 and H2 subgroups were going through a near neutral or neutral evolution and globally increased with time. Notably the frequency of H1 was generally high in Europe and correlated to death rate (r>0.37). Conclusions In this study, the evolution and molecular characteristics of more than 16000 genomic sequences provided a new perspective for revealing epidemiology of SARS-CoV-2.

Comprehensive evolution and molecular characteristics of a large number of SARS-CoV-2 genomes revealed its epidemic trend and possible origins

SARS-CoV, as the pathogeny of severe acute respiratory syndrome (SARS), is a mystery that the origin of the virus is still unknown even a few isolates of the virus were completely sequenced. To explore the genesis of SARS-CoV, the FDOD method previously developed by us was applied to comparing complete genomes from 12 SARS-CoV isolates to those from 12 previously identified coronaviruses and an unrooted phylogenetic tree was constructed. Our results show that all SARS-CoV isolates were clustered into a clique and previously identified coronaviruses formed the other clique. Meanwhile, the three groups of coronaviruses depart from each other clearly in our tree that is consistent with the results of prevenient papers. Differently, from the topology of the phylogenetic tree we found that SARS-CoV is more close to group 1 within genus coronavirus. The topology map also shows that the 12 SARS-CoV isolates may be divided into two groups determined by the association with the SARS-CoV from the Hotel M in Hong Kong that may give some information about the infectious relationship of the SARS.

Phylogeny of SARS-CoV as inferred from complete genome comparison

The sudden emergence of severe respiratory disease, caused by a novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), has recently become a public health emergency. Genome sequence analysis of SARS-CoV-2 revealed its close resemblance to the earlier reported SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). However, initial testing of the drugs used against SARS-CoV and MERS-CoV has been ineffective in controlling SARS-CoV-2. The present review looks to highlight the differences in genomic, proteomic, pathogenesis, and therapeutic strategies of SARS-CoV-2. We have carried out sequence analysis of potential drug target proteins in SARS-CoV-2 and, compared them with SARS-CoV-1 and MERS viruses. Analysis of mutations in the coding and non-coding regions, genetic diversity, and pathogenicity of SARS-CoV-2 has also been done. A detailed structural analysis of drug target proteins was performed to gain insights into the mechanism of pathogenesis, structure-function relationships, and the development of structure-guided therapeutic approaches. The cytokine profiling and inflammatory signalling are different in the case of SARS-CoV-2 infection. We also highlighted possible therapies and their mechanism of action followed by clinical manifestation. Our analysis suggests a minimal variation in the genome sequence of SARS-CoV-2, may be responsible for a drastic change in the structures of target proteins, makes available drugs ineffective.

The pandemic COVID-19 caused by the zoonotic virus SARS-CoV-2 has devastated countries worldwide, infecting more than 4.5 million people and leading to more than 300,000 deaths. Whole genome sequencing (WGS) is an effective tool to monitor emerging strains and provide information for intervention, thus help to inform outbreak control decisions. Here, we reported the first effort to sequence and de novo assemble the whole genome of SARS-CoV-2 using PacBio’s SMRT sequencing technology in Vietnam. We also presented the annotation results and a brief analysis of the variants found in our SARS-CoV-2 strain, which was isolated from a Vietnamese patient. The sequencing was successfully completed and de novo assembled in less than 30 hours, resulting in one contig with no gap and a length of 29,766 bp. All detected variants as compared to the NCBI reference were highly accurate as confirmed by Sanger sequencing. The results have shown the potential of long read sequencing to provide high quality WGS data to support public health responses, and advance understanding of this and future pandemics.

WHOLE-GENOME SEQUENCING AND DE NOVO ASSEMBLY OF A 2019 NOVEL CORONAVIRUS (SARS-COV-2) STRAIN ISOLATED IN VIETNAM

During its first two and a half months, the recently emerged 2019 novel coronavirus, SARS-CoV-2, has already infected over one-hundred thousand people worldwide and has taken more than four thousand lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge, we leveraged data about the related coronaviruses that is readily available in public databases and integrated these data into a single computational pipeline. As a result, we provide comprehensive structural genomics and interactomics roadmaps of SARS-CoV-2 and use this information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community.

Structural Genomics of SARS-CoV-2 Indicates Evolutionary Conserved Functional Regions of Viral Proteins

Knowledge of the evolution of pathogens is of great medical and biological significance to the prevention, diagnosis, and therapy of infectious diseases. In order to understand the origin and evolution of the SARS-CoV (severe acute respiratory syndrome-associated coronavirus), we collected complete genome sequences of all viruses available in GenBank, and made comparative analyses with the SARS-CoV. Genomic signature analysis demonstrates that the coronaviruses all take the TGTT as their richest tetranucleotide except the SARS-CoV. A detailed analysis of the forty-two complete SARS-CoV genome sequences revealed the existence of two distinct genotypes, and showed that these isolates could be classified into four groups. Our manual analysis of the BLASTN results demonstrates that the HE (hemagglutinin-esterase) gene exists in the SARS-CoV, and many mutations made it unfamiliar to us.

Evolution and Variation of the SARS-CoV Genome

To investigate the evolutionary history of the current pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a total of 137 genomes of coronavirus strains with release dates between January 2019 and 25 March 2020, were analyzed. To investigate the potential intermediate host of the SARS-CoV-2, we analyzed spike glycoprotein sequences from different animals, with particular emphasis on bats. We performed phylogenetic analysis and structural reconstruction of the spike glycoproteins with subsequent alignment and comparison. Our phylogenetic results revealed that SARS-CoV-2 was more similar to the bats' betacoronavirus isolates: HKU5-related from Pipistrellus abramus and HKU4-related from Tylonycteris pachypus. We also identified a yak betacoronavirus strain, YAK/HY24/CH/2017, as the closest match in the comparison of the structural models of spike glycoproteins. Interestingly, a set of unique features has been described for this particular strain of the yak betacoronavirus. Therefore, our results suggest that the human SARS-CoV-2, responsible for the current outbreak of COVID-19, could also come from yak as an intermediate host.

SARS-CoV-2: Structural diversity, phylogeny, and potential animal host identification of spike glycoprotein

BACKGROUND: More than two months separated the initial description of SARS-CoV-2 and discovery of its widespread dissemination in the United States. Despite this lengthy interval, implementation of specific quantitative reverse transcription (qRT)-PCR-based SARS-CoV-2 tests in the US has been slow, and testing is still not widely available. Metagenomic sequencing offers the promise of unbiased detection of emerging pathogens, without requiring prior knowledge of the identity of the responsible agent or its genomic sequence. METHODS: To evaluate metagenomic approaches in the context of the current SARS-CoV-2 epidemic, laboratory-confirmed positive and negative samples from Seattle, Washington were evaluated by metagenomic sequencing, with comparison to a 2019 reference genomic database created before the emergence of SARS-CoV-2. RESULTS: Within 36 hours our results showed clear identification of a novel human Betacoronavirus, closely related to known Betacoronaviruses of bats, in laboratory-proven cases of SARS-CoV-2. A subset of samples also showed superinfection or colonization with human parainfluenza virus 3 or Moraxella species, highlighting the need to test directly for SARS-CoV-2 as opposed to ruling out an infection using a viral respiratory panel. Samples negative for SARS-CoV-2 by RT-PCR were also negative by metagenomic analysis, and positive for Rhinovirus A and C. Unlike targeted SARS-CoV-2 qRT-PCR testing, metagenomic analysis of these SARS-CoV-2 negative samples identified candidate etiological agents for the patients’ respiratory symptoms. CONCLUSION: Taken together, these results demonstrate the value of metagenomic analysis in the monitoring and response to this and future viral pandemics.

Metagenomic analysis reveals clinical SARS-CoV-2 infection and bacterial or viral superinfection and colonization

Genomic analysis of SARS-CoV-2 sequences is crucial in determining the effectiveness of prudent safer at home measures in the United States (US). By haplotype analysis of 6,356 US isolates, we identified a pattern of strongly localized outbreaks at the city-, state-, and country-levels, and temporal transmissions. This points to the effectiveness of existing travel restriction policies and public health measures in controlling the transmission of SARS-CoV-2.

Comprehensive genome analysis of 6,000 USA SARS-CoV-2 isolates reveals haplotype signatures and localized transmission patterns by state and by country

The COVID-19 pandemic has spread across the globe at an alarming rate in the last four months. However, unlike any of the previous global outbreaks the availability of hundreds of SARS-CoV-2 sequences provides us with a unique opportunity to understand viral evolution in real time. We analysed 480 full-length (>29000 nt) sequences from the 1575 SARS-CoV-2 sequences available and identified 37 single-nucleotide substitutions occurring in >1% of the genomes. Majority of the substitutions were C to T or G to A. We identify C/Gs with an upstream TTT trinucleotide motif as hotspots for mutations in the SARS-CoV-2 genome. Interestingly, two of the 37 substitutions occur within highly conserved secondary structures in the 5’ and 3’ untranslated regions that are critical for the virus life cycle. Furthermore, clustering analysis revealed unique geographical distribution of SARS-CoV-2 variants defined by their mutation profile. Of note, we observed several co-occurring mutations that almost never occur individually. We define 3 mutually exclusive lineages (A1, B1 and C1) of SARS-CoV-2 which account for about three quarters of the genomes analysed. We identify lineage-defining leading mutations in the SARS-CoV-2 genome which precede the occurrence of sub-lineage defining trailing mutations. The identification of mutually exclusive lineage-defining mutations with geographically restricted patterns of distribution has potential implications for diagnosis, pathogenesis and vaccine design. Our work provides novel insights on the temporal evolution of SARS-CoV-2.

Mutation landscape of SARS-CoV-2 reveals three mutually exclusive clusters of leading and trailing single nucleotide substitutions

OBJECTIVE To perform variation and phylogenetics analysis on the SARS-CoV genome sequence (PUMC01) isolated in the Peking Union Medical College Hospital. METHODS The cDNA library of SARS-CoV (PUMC01 isolate) was constructed by means of random-priming strategy. Random selected plasmid was sequenced and the genome sequence of SARS-CoV-PUMC01 was assembled by conventional methods (The Genebank Accession No. of SARS-CoV-PUMC01 is AY350750). The variation and phylogenetics analysis were performed by comparing the PUMC01 sequence with other SARS-CoV isolates. RESULTS Ten variation sites were found by comparing PUMC01 isolate with Tor2 and Urbani isolates. In phylogenetic analysis of 18 SARS-CoV isolates, two classes were observed and there is different differential time between these two classes and the different isolates in each class. CONCLUSIONS The evidence of phylogenetic analysis of different SARS-CoV isolates from different region is instructive for understanding the clinical relations between the different isolates and the transmission chain of SARS-CoV.

[Analysis on the SARS-CoV genome of PUMC01 isolate].

Abstract The emerging global infectious COVID-19 disease by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) presents critical threats to global public health and the economy since it was identified in late December 2019 in China. The virus has gone through various pathways of evolution. To understand the evolution and transmission of SARS-CoV-2, genotyping of virus isolates is of great importance. This study presents an accurate method for effectively genotyping SARS-CoV-2 viruses using complete genomes. The method employs the multiple sequence alignments of the genome isolates with the SARS-CoV-2 reference genome. The single-nucleotide polymorphism (SNP) genotypes are then measured by Jaccard distances to track the relationship of virus isolates. The genotyping analysis of SARS-CoV-2 isolates from the globe reveals that specific multiple mutations are the predominated mutation type during the current epidemic. The proposed method serves an effective tool for monitoring and tracking the epidemic of pathogenic viruses in their global and local genetic variations. The genotyping analysis shows that the genes encoding the S proteins and RNA polymerase, RNA primase, and nucleoprotein, undergo frequent mutations. These mutations are critical for vaccine development in disease control.

Genotyping coronavirus SARS-CoV-2: Methods and implications

The rooting of the SARS-CoV-2 phylogeny is important for understanding the origin and early spread of the virus. Previously published phylogenies have used different rootings that do not always provide consistent results. We use several different strategies for rooting the SARS-CoV-2 tree and provide measures of statistical uncertainty for all methods. We show that methods based on the molecular clock tend to place the root in the B clade, while methods based on outgroup rooting tend to place the root in the A clade. The results from the two approaches are statistically incompatible, possibly as a consequence of deviations from a molecular clock or excess back-mutations. We also show that none of the methods provide strong statistical support for the placement of the root in any particular edge of the tree. Our results suggest that inferences on the origin and early spread of SARS-CoV-2 based on rooted trees should be interpreted with caution.

Assessing uncertainty in the rooting of the SARS-CoV-2 phylogeny

Here we aim to describe early mutational events across samples from publicly available SARS-CoV-2 sequences from the sequence read archive repository. Up until March 27, 2020, we downloaded 53 illumina datasets, mostly from China, USA (Washington DC) and Australia (Victoria). Of 30 high quality datasets, 27 datasets (90%) contain at least a single founder mutation and most of the variants are missense (over 63%). Five-point mutations with clonal (founder) effect were found in USA sequencing samples. Sequencing samples from USA in GenBank present this signature with 50% allele frequencies among samples. Australian mutation signatures were more diverse than USA samples, but still, clonal events were found in those samples. Mutations in the helicase and orf1a coding regions from SARS-CoV-2 were predominant, among others, suggesting that these proteins are prone to evolve by natural selection. Finally, we firmly urge that primer sets for diagnosis be carefully designed, since rapidly occurring variants would affect the performance of the reverse transcribed quantitative PCR (RT-qPCR) based viral testing.

Direct massively parallel sequencing of SARS-CoV-2 genome was undertaken from nasopharyngeal and oropharyngeal swab samples of infected individuals in Eastern India. Seven of the isolates belonged to the A2a clade, while one belonged to the B4 clade. Specific mutations, characteristic of the A2a clade, were also detected, which included the P323L in RNA-dependent RNA polymerase and D614G in the Spike glycoprotein. Further, our data revealed emergence of novel subclones harbouring nonsynonymous mutations, viz. G1124V in Spike (S) protein, R203K, and G204R in the nucleocapsid (N) protein. The N protein mutations reside in the SR-rich region involved in viral capsid formation and the S protein mutation is in the S(2) domain, which is involved in triggering viral fusion with the host cell membrane. Interesting correlation was observed between these mutations and travel or contact history of COVID-19 positive cases. Consequent alterations of miRNA binding and structure were also predicted for these mutations. More importantly, the possible implications of mutation D614G (in S(D) domain) and G1124V (in S(2) subunit) on the structural stability of S protein have also been discussed. Results report for the first time a bird’s eye view on the accumulation of mutations in SARS-CoV-2 genome in Eastern India. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12038-020-00046-1) contains supplementary material, which is available to authorized users.

Mutations in SARS-CoV-2 viral RNA identified in Eastern India: Possible implications for the ongoing outbreak in India and impact on viral structure and host susceptibility

The outbreak of COVID-19 started in mid-December 2019 in Wuhan, China. Up to 29 February 2020, SARS-CoV-2 (HCoV-19 / 2019-nCoV) had infected more than 85 000 people in the world. In this study, we used 93 complete genomes of SARS-CoV-2 from the GISAID EpiFlu TM database to investigate the evolution and human-to-human transmissions of SARS-CoV-2 in the first two months of the outbreak. We constructed haplotypes of the SARS-CoV-2 genomes, performed phylogenomic analyses and estimated the potential population size changes of the virus. The date of population expansion was calculated based on the expansion parameter tau ( τ) using the formula t= τ/2 u. A total of 120 substitution sites with 119 codons, including 79 non-synonymous and 40 synonymous substitutions, were found in eight coding-regions in the SARS-CoV-2 genomes. Forty non-synonymous substitutions are potentially associated with virus adaptation. No combinations were detected. The 58 haplotypes (31 found in samples from China and 31 from outside China) were identified in 93 viral genomes under study and could be classified into five groups. By applying the reported bat coronavirus genome (bat-RaTG13-CoV) as the outgroup, we found that haplotypes H13 and H38 might be considered as ancestral haplotypes, and later H1 was derived from the intermediate haplotype H3. The population size of the SARS-CoV-2 was estimated to have undergone a recent expansion on 06 January 2020, and an early expansion on 08 December 2019. Furthermore, phyloepidemiologic approaches have recovered specific directions of human-to-human transmissions and the potential sources for international infected cases.

Decoding the evolution and transmissions of the novel pneumonia coronavirus (SARS-CoV-2 / HCoV-19) using whole genomic data

BACKGROUND China announced an outbreak of new coronavirus in the city of Wuhan on December 31, 2019; lash to now, the virus transmission has become pandemic worldwide. Severe cases from Huanan Seafood Wholesale market in Wuhan were confirmed pneumonia with a novel coronavirus. (2019-nCoV). Understanding the molecular mechanisms of genome selection and packaging is critical for developing antiviral strategies. Thus, we defined the correlation in ten SARS-CoV2 sequences from different countries to analyze the genomic patterns of disease origin and evolution aiming for development new control pandemic processes. METHODS We apply genomic analysis to observe SARS-Co-V2 sequences from GenBank (http:// www.ncbi.nim.nih.gov/genebank/): MN 908947 China, C1), MN985325 (USA:WA, UW), MN996527 (China, C2), MT007544 (Australia:Victoria, A1), MT027064 (USA:CA, UC), MT039890 (South Korea, K1), MT066175 (Taiwan,T1), MT066176 (Taiwan, T2), LC528232 (Japan, J1), and LC528233 (Japan, J2) for genomic sequence alignment an analysis. Multiple Sequence Alignment by Clustalw (https://www.genome.jp/tools-bin/clustalw) web is applied as our alignment tool. RESULTS We analyze ten sequences from NCBI database by genome alignment and find no difference in amino acid sequences within M and N proteins. There are two amino acid variances in Spike protein region. One mutation found from south Korea sequence is verified. Two possible "L" and "S" SNP found in ORF1ab and ORF8 regions are detected CONCLUSION:: We perform genomic analysis and comparative multiple sequence of SARS-CoV-2. Studies about the biological symptoms of SARS-CoV-2 in clinic animal and humans will manipulate an understanding the origin of pandemic crisis.

Genomic Analysis and Comparative Multiple Sequence of SARS-CoV2.

A coding-complete genome sequence of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolate was revealed. The sample for the virus was isolated from a female patient from Dhaka, Bangladesh, suffering from coronavirus disease-2019 (COVID-19).

Coding-Complete Genome Sequence of SARS-CoV-2 Isolate from Bangladesh by Sanger Sequencing.

The outbreak of COVID-19 started in mid-December 2019 in Wuhan, China. Up to 29 February 2020, SARS-CoV-2 (HCoV-19 / 2019-nCoV) had infected more than 85 000 people in the world. In this study, we used 93 complete genomes of SARS-CoV-2 from the GISAID EpiFlu(TM) database to investigate the evolution and human-to-human transmissions of SARS-CoV-2 in the first two months of the outbreak. We constructed haplotypes of the SARS-CoV-2 genomes, performed phylogenomic analyses and estimated the potential population size changes of the virus. The date of population expansion was calculated based on the expansion parameter tau (τ) using the formula t=τ/2u. A total of 120 substitution sites with 119 codons, including 79 non-synonymous and 40 synonymous substitutions, were found in eight coding-regions in the SARS-CoV-2 genomes. Forty non-synonymous substitutions are potentially associated with virus adaptation. No combinations were detected. The 58 haplotypes (31 found in samples from China and 31 from outside China) were identified in 93 viral genomes under study and could be classified into five groups. By applying the reported bat coronavirus genome (bat-RaTG13-CoV) as the outgroup, we found that haplotypes H13 and H38 might be considered as ancestral haplotypes, and later H1 was derived from the intermediate haplotype H3. The population size of the SARS-CoV-2 was estimated to have undergone a recent expansion on 06 January 2020, and an early expansion on 08 December 2019. Furthermore, phyloepidemiologic approaches have recovered specific directions of human-to-human transmissions and the potential sources for international infected cases.

A novel coronavirus has been identified as the cause of the outbreak of severe acute respiratory syndrome (SARS). Previous phylogenetic analyses based on sequence alignments show that SARS‐CoVs form a new group distantly related to the other three groups of previously characterized coronaviruses. In this aritcle, a new approach based on the 2D graphical representation of the whole genome sequence is proposed to analyze the phylogenetic relationships of coronaviruses. The evolutionary distances are obtained through measuring the differences among the two‐dimensional curves. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1196–1202, 2006

Coronavirus phylogeny based on 2D graphical representation of DNA sequence

During its first two and a half months, the recently emerged 2019 novel coronavirus, SARS-CoV-2, has already infected over one-hundred thousand people worldwide and has taken more than four thousand lives However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop To expedite the advancement of our knowledge, we leveraged data about the related coronaviruses that is readily available in public databases and integrated these data into a single computational pipeline As a result, we provide comprehensive structural genomics and interactomics roadmaps of SARS-CoV-2 and use this information to infer the possible functional differences and similarities with the related SARS coronavirus All data are made publicly available to the research community

The recent global outbreak of viral pneumonia designated as Coronavirus Disease 2019 (COVID-19) by coronavirus (SARS-CoV-2) has threatened global public health and urged to investigate its source. Whole genome analysis of SARS-CoV-2 revealed ~96% genomic similarity with bat CoV (RaTG13) and clustered together in phylogenetic tree. Furthermore, RaTGl3 also showed 97.43% spike protein similarity with SARS-CoV-2 suggesting that RaTGl3 is the closest strain. However, RBD and key amino acid residues supposed to be crucial for human-to-human and cross-species transmission are homologues between SARS-CoV-2 and pangolin CoVs. These results from our analysis suggest that SARS-CoV-2 is a recombinant virus of bat and pangolin CoVs. Moreover, this study also reports mutations in coding regions of 125 SARS-CoV-2 genomes signifying its aptitude for evolution. In short, our findings propose that homologous recombination has been occurred between bat and pangolin CoVs that triggered cross-species transmission and emergence of SARS-CoV-2, and, during the ongoing outbreak, SARS-CoV-2 is still evolving for its adaptability.

Evidence of the Recombinant Origin and Ongoing Mutations in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

World Health Organization (WHO) declared COVID-19 as a pandemic disease on March 11, 2020. Comparison of genome sequences from diverse locations allows us to identify the genetic diversity among viruses which would help in ascertaining viral virulence, disease pathogenicity, origin and spread of the SARS-CoV-2 between countries. The aim of this study is to ascertain the genetic diversity among Indian SARS-CoV-2 isolates. Initial examination of the phylogenetic data of SARS-CoV-2 genomes (n=3123) from different continents deposited at GISAID (Global Initiative on Sharing All Influenza Data) revealed multiple origin for Indian isolates. An in-depth analysis of 449 viral genomes derived from samples representing countries from USA, Europe, China, East Asia, South Asia, Oceania, Middle East regions and India revealed that most Indian samples are divided into two clusters (A and B) with cluster A showing more similarity to samples from Oceania and Kuwait and the cluster B grouping with countries from Europe, Middle East and South Asia. Diversity analysis of viral clades, which are characterized by specific non-synonymous mutations in viral proteins, discovered that the cluster A Indian samples belong to I clade (V378I in ORF1ab), which is an Oceania clade with samples having Iran connections and the cluster B Indian samples belong to G clade (D614G in Spike protein), which is an European clade. Thus our study identifies that the Indian SARS-CoV-2 viruses belong to I and G clades with potential origin to be countries mainly from Oceania, Europe, Middle East and South Asia regions, which strongly implying the spread of virus through most travelled countries. The study also emphasizes the importance of pathogen genomics through phylogenetic analysis to discover viral genetic diversity and understand the viral transmission dynamics with eventual grasp on viral virulence and disease pathogenesis.

Genomics of Indian SARS-CoV-2: Implications in genetic diversity, possible origin and spread of virus

One of the reasons for the fast spread of SARS-CoV-2 is the lack of accuracy in detection tools in the clinical field. Molecular techniques, such as quantitative real-time RT-PCR and nucleic acid sequencing methods, are widely used to identify pathogens. For this particular virus, however, they have an overall unsatisfying detection rate, due to its relatively recent emergence and still not completely understood features. In addition, SARS-CoV-2 is remarkably similar to other Coronaviruses, and it can present with other respiratory infections, making identification even harder. To tackle this issue, we propose an assisted detection test, combining molecular testing with deep learning. The proposed approach employs a state-of-the-art deep convolutional neural network, able to automatically create features starting from the genome sequence of the virus. Experiments on data from the Novel Coronavirus Resource (2019nCoVR) show that the proposed approach is able to correctly classify SARS-CoV-2, distinguishing it from other coronavirus strains, such as MERS-CoV, HCoV-NL63, HCoV-OC43, HCoV-229E, HCoV-HKU1, and SARS-CoV regardless of missing information and errors in sequencing (noise). From a dataset of 553 complete genome non-repeated sequences that vary from 1,260 to 31,029 bps in length, the proposed approach classifies the different coronaviruses with an average accuracy of 98.75% in a 10-fold cross-validation, identifying SARS-CoV-2 with an AUC of 98%, specificity of 0.9939 and sensitivity of 1.00 in a binary classification. Then, using the same basis, we classify SARS-CoV-2 from 384 complete viral genome sequences with human host, that contain the gene ORF1ab from the NCBI with a 10-fold accuracy of 98.17%, a specificity of 0.9797 and sensitivity of 1.00. Furthermore, an in-depth analysis of the results allow us to identify base pairs sequences that are unique to SARS-CoV-2 and do not appear in other virus strains, that could then be used as a base for designing new primers and examined by experts to extract further insights. These preliminary results seem encouraging enough to identify deep learning as a promising research venue to develop assisted detection tests for SARS-CoV-2. At this end the interaction between viromics and deep learning, will hopefully help to solve global infection problems. In addition, we offer our code and processed data to be used for diagnostic purposes by medical doctors, virologists and scientists involved in solving the SARS-CoV-2 pandemic. As more data become available we will update our system.

Accurate Identification of SARS-CoV-2 from Viral Genome Sequences using Deep Learning

We describe fifteen major mutation events from 2,058 high-quality SARS-CoV-2 genomes deposited up to March 31st, 2020. These events define five major clades (G, I, S, D and V) of globally-circulating viral populations, representing 85.7% of all sequenced cases, which we can identify using a 10 nucleotide genetic classifier or barcode. We applied this barcode to 4,000 additional genomes deposited between March 31st and April 15th and classified successfully 95.6% of the clades demonstrating the utility of this approach. An analysis of amino acid variation in SARS-CoV-2 ORFs provided evidence of substitution events in the viral proteins involved in both host-entry and genome replication. The systematic monitoring of dynamic changes in the SARS-CoV-2 genomes of circulating virus populations over time can guide therapeutic and prophylactic strategies to manage and contain the virus and, also, with available efficacious antivirals and vaccines, aid in the monitoring of circulating genetic diversity as we proceed towards elimination of the agent. The barcode will add the necessary genetic resolution to facilitate tracking and monitoring of infection clusters to distinguish imported and indigenous cases and thereby aid public health measures seeking to interrupt transmission chains without the requirement for real-time complete genomes sequencing.

The genomic variation landscape of globally-circulating clades of SARS-CoV-2 defines a genetic barcoding scheme

Tracing the history of molecular changes in coronaviruses using phylogenetic methods can provide powerful insights into the patterns of modification to sequences that underlie alteration to selective pressure and molecular function in the SARS-CoV (severe acute respiratory syndrome coronavirus) genome. The topology and branch lengths of the phylogenetic relationships among the family Coronaviridae, including SARS-CoV, have been estimated using the replicase polyprotein. The spike protein fragments S1 (involved in receptor-binding) and S2 (involved in membrane fusion) have been found to have different mutation rates. Fragment S1 can be further divided into two regions (S1A, which comprises approximately the first 400 nucleotides, and S1B, comprising the next 280) that also show different rates of mutation. The phylogeny presented on the basis of S1B shows that SARS-CoV is closely related to MHV (murine hepatitis virus), which is known to bind the murine receptor CEACAM1. The predicted structure, accessibility and mutation rate of the S1B region is also presented. Because anti-SARS drugs based on S2 heptads have short half-lives and are difficult to manufacture, our findings suggest that the S1B region might be of interest for anti-SARS drug discovery.

Phylogenomics and bioinformatics of SARS-CoV

SARS-CoV-2 is a betacoronavirus that is responsible for the COVID-19 pandemic. The genome of SARS-CoV-2 was reported recently, but its transcriptomic architecture is unknown. Utilizing two complementary sequencing techniques, we here present a high-resolution map of the SARS-CoV-2 transcriptome and epitranscriptome. DNA nanoball sequencing shows that the transcriptome is highly complex owing to numerous recombination events, both canonical and noncanonical. In addition to the genomic RNA and subgenomic RNAs common in all coronaviruses, SARS-CoV-2 produces a large number of transcripts encoding unknown ORFs with fusion, deletion, and/or frameshift. Using nanopore direct RNA sequencing, we further find at least 41 RNA modification sites on viral transcripts, with the most frequent motif being AAGAA. Modified RNAs have shorter poly(A) tails than unmodified RNAs, suggesting a link between the internal modification and the 3′ tail. Functional investigation of the unknown ORFs and RNA modifications discovered in this study will open new directions to our understanding of the life cycle and pathogenicity of SARS-CoV-2. Highlights We provide a high-resolution map of SARS-CoV-2 transcriptome and epitranscriptome using nanopore direct RNA sequencing and DNA nanoball sequencing. The transcriptome is highly complex owing to numerous recombination events, both canonical and noncanonical. In addition to the genomic and subgenomic RNAs common in all coronaviruses, SARS-CoV-2 produces transcripts encoding unknown ORFs. We discover at least 41 potential RNA modification sites with an AAGAA motif.

The architecture of SARS-CoV-2 transcriptome

Human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is most closely related, by average genetic distance, to two coronaviruses isolated from bats, RaTG13 and RmYN02. However, there is a segment of high amino acid similarity between human SARS-CoV-2 and a pangolin isolated strain, GD410721, in the receptor binding domain (RBD) of the spike protein, a pattern that can be caused by either recombination or by convergent amino acid evolution driven by natural selection. We perform a detailed analysis of the synonymous divergence, which is less likely to be affected by selection than amino acid divergence, between human SARS-CoV-2 and related strains. We show that the synonymous divergence between the bat derived viruses and SARS-CoV-2 is larger than between GD410721 and SARS-CoV-2 in the RBD, providing strong additional support for the recombination hypothesis. However, the synonymous divergence between pangolin strain and SARS-CoV-2 is also relatively high, which is not consistent with a recent recombination between them, instead it suggests a recombination into RaTG13. We also find a 14-fold increase in the dN/dS ratio from the lineage leading to SARS-CoV-2 to the strains of the current pandemic, suggesting that the vast majority of non-synonymous mutations currently segregating within the human strains have a negative impact on viral fitness. Finally, we estimate that the time to the most recent common ancestor of SARS-CoV-2 and RaTG13 or RmYN02 based on synonymous divergence, is 51.71 years (95% C.I., 28.11-75.31) and 37.02 years (95% C.I., 18.19-55.85), respectively.

Synonymous mutations and the molecular evolution of SARS-Cov-2 origins

Direct massively parallel sequencing of SARS-CoV-2 genome was undertaken from nasopharyngeal and oropharyngeal swab samples of infected individuals in Eastern India. Seven of the isolates belonged to the A2a clade, while one belonged to the B4 clade. Specific mutations, characteristic of the A2a clade, were also detected, which included the P323L in RNA-dependent RNA polymerase and D614G in the Spike glycoprotein. Further, our data revealed emergence of novel subclones harbouring nonsynonymous mutations, viz. G1124V in Spike (S) protein, R203K, and G204R in the nucleocapsid (N) protein. The N protein mutations reside in the SR-rich region involved in viral capsid formation and the S protein mutation is in the S2 domain, which is involved in triggering viral fusion with the host cell membrane. Interesting correlation was observed between these mutations and travel or contact history of COVID-19 positive cases. Consequent alterations of miRNA binding and structure were also predicted for these mutations. More importantly, the possible implications of mutation D614G (in SD domain) and G1124V (in S2 subunit) on the structural stability of S protein have also been discussed. Results report for the first time a bird's eye view on the accumulation of mutations in SARS-CoV-2 genome in Eastern India.

Mutations in SARS-CoV-2 viral RNA identified in Eastern India: Possible implications for the ongoing outbreak in India and impact on viral structure and host susceptibility.

Background SARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines. Methods We used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure. Results We used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades. Conclusion The worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.

Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world

Background With the gradual reopening of economies and resumption of social life, robust surveillance mechanisms should be implemented to control the ongoing COVID-19 pandemic. Unlike RT-qPCR, SARS-CoV-2 Whole Genome Sequencing (cWGS) has the added advantage of identifying cryptic origins of the virus, and the extent of community-based transmissions versus new viral introductions, which can in turn influence public health policy decisions. However, practical and cost considerations of cWGS should be addressed before it can be widely implemented. Methods We performed shotgun transcriptome sequencing using RNA extracted from nasopharyngeal swabs of patients with COVID-19, and compared it to targeted SARS-CoV-2 full genome amplification and sequencing with respect to virus detection, scalability, and cost-effectiveness. To track virus origin, we used open-source multiple sequence alignment and phylogenetic tools to compare the assembled SARS-CoV-2 genomes to publicly available sequences. Results We show a significant improvement in whole genome sequencing data quality and viral detection using amplicon-based target enrichment of SARS-CoV-2. With enrichment, more than 99% of the sequencing reads mapped to the viral genome compared to an average of 0.63% without enrichment. Consequently, a dramatic increase in genome coverage was obtained using significantly less sequencing data, enabling higher scalability and significant cost reductions. We also demonstrate how SARS-CoV-2 genome sequences can be used to determine their possible origin through phylogenetic analysis including other viral strains. Conclusions SARS-CoV-2 whole genome sequencing is a practical, cost-effective, and powerful approach for population-based surveillance and control of viral transmission in the next phase of the COVID-19 pandemic.

SARS-CoV-2 Whole Genome Amplification and Sequencing for Effective Population-Based Surveillance and Control of Viral Transmission

The complete genome sequence of a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) isolate obtained from a nasopharyngeal swab from a patient with COVID-19 in Bangladesh is reported.

Complete Genome Sequence of a Novel Coronavirus (SARS-CoV-2) Isolate from Bangladesh

Covid-19 pandemic, caused by the sars-cov-2 strain of coronavirus, has affected millions of people all over the world and taken thousands of lives. It is of utmost importance that the character of this deadly virus be studied and its nature be analysed. We present here an analysis pipeline comprising phylogenetic analysis on strains of this novel virus to track its evolutionary history among the countries uncovering several interesting relationships, followed by a classification exercise to identify the virulence of the strains and extraction of important features from its genetic material that are used subsequently to predict mutation at those interesting sites using deep learning techniques. In a nutshell, we have prepared an analysis pipeline for hCov genome sequences leveraging the power of machine intelligence and uncovered what remained apparently shrouded by raw data.

Analyzing hCov genome sequences: Applying Machine Intelligence and beyond