Identification of novel bat coronaviruses sheds light on the evolutionary origins of SARS-CoV-2 and related viruses (preprint)

Although a variety of SARS-CoV-2 related coronaviruses have been identified, the evolutionary origins of this virus remain elusive. We describe a meta-transcriptomic study of 411 samples collected from 23 bat species in a small (~1100 hectare) region in Yunnan province, China, from May 2019 to November 2020. We identified coronavirus contigs in 40 of 100 sequencing libraries, including seven representing SARS-CoV-2-like contigs. From these data we obtained 24 full-length coronavirus genomes, including four novel SARS-CoV-2 related and three SARS-CoV related genomes. Of these viruses, RpYN06 exhibited 94.5% sequence identity to SARS-CoV-2 across the whole genome and was the closest relative of SARS-CoV-2 in the ORF1ab, ORF7a, ORF8, N, and ORF10 genes. The other three SARS-CoV-2 related coronaviruses were nearly identical in sequence and clustered closely with a virus previously identified in pangolins from Guangxi, China, although with a genetically distinct spike gene sequence. We also identified 17 alphacoronavirus genomes, including those closely related to swine acute diarrhea syndrome virus and porcine epidemic diarrhea virus. Ecological modeling predicted the co-existence of up to 23 Rhinolophus bat species in Southeast Asia and southern China, with the largest contiguous hotspots extending from South Lao and Vietnam to southern China. Our study highlights both the remarkable diversity of bat viruses at the local scale and that relatives of SARS-CoV-2 and SARS-CoV circulate in wildlife species in a broad geographic region of Southeast Asia and southern China. These data will help guide surveillance efforts to determine the origins of SARS-CoV-2 and other pathogenic coronaviruses.

Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2Population Bottlenecks and Intra-host Evolution during Human-to-Human Transmission of SARS-CoV-2 (preprint)

The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Author summaryIn this study, we compared SARS-CoV-2 populations of 13 Chinese COVID-19 patients. Those viral populations contained a considerable proportion of viral sub-genomic messenger RNAs (sgmRNA), reflecting an active viral replication activity in the respiratory tract tissues. The comparison of 66 identified intra-host variants further showed a low viral genetic distance between intra-household patients and a narrow transmission bottleneck size. Despite the co-existence of genetically distinct viruses within the same host, most intra-host minor variants were not shared between transmission pairs, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions. Furthermore, the narrow bottleneck and active viral activity in the respiratory tract show that the passage of a small number of virions can cause infection. Our data have therefore delivered a key genomic resource for the SARS-CoV-2 transmission research and enhanced our understanding of the evolutionary dynamics of SARS-CoV-2.

Intra-host Variation and Evolutionary Dynamics of SARS-CoV-2 Population in COVID-19 Patients (preprint)

As of middle May 2020, the causative agent of COVID-19, SARS-CoV-2, has infected over 4 million people with more than 300 thousand death as official reports1,2. The key to understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of mutation and evolution of this virus at both inter- and intra-host levels. However, despite quite a few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and their evolutionary dynamics remain mostly unknown. Here, using deep sequencing data, we achieved and characterized consensus genomes and intra-host genomic variants from 32 serial samples collected from eight patients with COVID-19. The 32 consensus genomes revealed the coexistence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparison of allele frequencies of the iSNVs revealed genetic divergence between intra-host populations of the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events among intra-host transmissions. Nonetheless, we observed a maintained viral genetic diversity within GIT, showing an increased population with accumulated mutations developed in the tissue-specific environments. The iSNVs identified here not only show spatial divergence of intra-host viral populations, but also provide new insights into the complex virus-host interactions.

Multiple approaches for massively parallel sequencing of HCoV-19 genomes directly from clinical samples (preprint)

COVID-19 has caused a major epidemic worldwide, however, much is yet to be known about the epidemiology and evolution of the virus. One reason is that the challenges underneath sequencing HCoV-19 directly from clinical samples have not been completely tackled. Here we illustrate the application of amplicon and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of HCoV-19 from clinical samples covering a range of sample types and viral load. We also examine and compare the bias, sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. This is, to date, the first work systematically implements amplicon and capture approaches in sequencing HCoV-19, as well as the first comparative study across methods. Our work offers practical solutions for genome sequencing and analyses of HCoV-19 and other emerging viruses.