Background: COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. Methods: We applied a novel multiplex PCR amplicon (amplicon)-based 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 SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner.

Background Since early February 2021, the causative agent of COVID-19, SARS-CoV-2, has infected over 104 million people with more than 2 million deaths according to official reports. 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. Methods Using high-throughput sequencing of metatranscriptomic and hybrid captured libraries, we characterized consensus genomes and intra-host single nucleotide variations (iSNVs) of serial samples collected from eight patients with COVID-19. The distribution of iSNVs along the SARS-CoV-2 genome was analyzed and co-occurring iSNVs among COVID-19 patients were identified. We also compared the evolutionary dynamics of SARS-CoV-2 population in the respiratory tract (RT) and gastrointestinal tract (GIT). Results The 32 consensus genomes revealed the co-existence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in a single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparing allele frequencies of the iSNVs revealed a clear genetic differentiation between intra-host populations from the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events during intra-host migrations. Compared to RT populations, the GIT populations showed a better maintenance and rapid development of viral genetic diversity following the suspected intra-host bottlenecks. Conclusions Our findings here illustrate the intra-host bottlenecks and evolutionary dynamics of SARS-CoV-2 in different anatomic sites and may provide new insights to understand the virus-host interactions of coronaviruses and other RNA viruses.

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.

49As of middle May 2020, the causative agent of COVID-19, SARS-CoV-2, has infected over 4 50 million people with more than 300 thousand death as official reports 1,2 . The key to 51 understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of 52 mutation and evolution of this virus at both inter-and intra-host levels. However, despite quite a 53 few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and 54 their evolutionary dynamics remain mostly unknown. Here, using deep sequencing data, we 55 achieved and characterized consensus genomes and intra-host genomic variants from 32 serial 56 samples collected from eight patients with COVID-19. The 32 consensus genomes revealed the 57 coexistence of different genotypes within the same patient. We further identified 40 intra-host 58 single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in single patient, while ten 59 iSNVs were found in at least two patients or identical to consensus variants. Comparison of 60 allele frequencies of the iSNVs revealed genetic divergence between intra-host populations of 61 the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events 62 among intra-host transmissions. Nonetheless, we observed a maintained viral genetic diversity 63 within GIT, showing an increased population with accumulated mutations developed in the 64 tissue-specific environments. The iSNVs identified here not only show spatial divergence of 65 intra-host viral populations, but also provide new insights into the complex virus-host 66 interactions. 67 68 MAIN 69 From January 25 to February 10 in 2020, we collected a total of 62 serial clinical samples from70 eight hospitalized patients (GZMU cohort) confirmed with SARS-CoV-2 infection using real-time 71 RT-qPCR (Table S1). All patients had direct contacts with confirmed cases during the early 72 stage of the outbreak. Most patients, except P15 and P62, had severe symptoms and received 73 mechanical ventilation in ICU, including the patient P01 who passed away eventually. The 74 4 patient P01 also showed much lower antibody (IgG and IgM) responses (Table S1) compared 75 to other patients. We then deep sequenced the 62 clinical samples using metatranscriptomic 76 and/or hybrid capture methods ( Table S1). The numbers of SARS-CoV-2 reads per million 77 (SARS-CoV-2 RPM) among the metatranscriptomic data correlated well with the corresponding 78 RT-qPCR cycle threshold (Ct), reflecting a robust estimation of viral load (R = 0.71, P = 6.7e-11) 79 ( Fig. 1a). The respiratory tract (RT: Nose, Sputum, Throat) and gastrointestinal tract (GIT: Anus, 80 Feces) samples showed higher SARS-CoV-2 RPMs compared to gastric mucosa and urine 81 samples (Fig. 1b). Furthermore, RT and GIT samples from two patients with mild symptoms 82 showed relatively low viral loads among their respective sample types. The data here may 83 reflect an active replication of SARS-CoV-2 in RT and GIT, especially in patients with severe 84 sympto...

38COVID-19 has caused a major epidemic worldwide, however, much is yet to be known 39 about the epidemiology and evolution of the virus. One reason is that the challenges 40 underneath sequencing HCoV-19 directly from clinical samples have not been com-41 pletely tackled. Here we illustrate the application of amplicon and hybrid capture (cap-42 ture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) 43 sequencing in retrieving complete genomes, inter-individual and intra-individual var-44 iations of HCoV-19 from clinical samples covering a range of sample types and viral 45load. We also examine and compare the bias, sensitivity, accuracy, and other char-46 acteristics of these approaches in a comprehensive manner. This is, to date, the first 47