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.

To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019‐nCoV outbreak in China and beyond, a total of 32 genomes of virus strains sampled from China, Thailand, and the USA with sampling dates between 24 December 2019 and 23 January 2020 were analyzed. Phylogenetic, transmission network, and likelihood‐mapping analyses of the genome sequences were performed. On the basis of the likelihood‐mapping analysis, the increasing tree‐like signals (from 0% to 8.2%, 18.2%, and 25.4%) over time may be indicative of increasing genetic diversity of 2019‐nCoV in human hosts. We identified three phylogenetic clusters using the Bayesian inference framework and three transmission clusters using transmission network analysis, with only one cluster identified by both methods using the above genome sequences of 2019‐nCoV strains. The estimated mean evolutionary rate for 2019‐nCoV ranged from 1.7926 × 10⁻³ to 1.8266 × 10⁻³ substitutions per site per year. On the basis of our study, undertaking epidemiological investigations and genomic data surveillance could positively impact public health in terms of guiding prevention efforts to reduce 2019‐nCOV transmission in real‐time.

To investigate the genetic diversity, spatiotemporal dynamics, and transmission networks of HIV-1 CRF55_01B epidemic in China. A total of 209 partial pol gene sequences of HIV-1 CRF55_01B were sampled during 2007–2015 from 7 provinces of China. Phylogenetic analyses and trait diffusion process of these sequences were performed using Bayesian methods. Distance-based molecular network analyses were performed to infer putative relationships. Characteristics of genetically linked individuals were analyzed. Our study identified that HIV-1 CRF55_01B likely originated among men who have sex with men (MSM) in Guangdong province in January 2003 (April 2000–April 2005), and that Guangdong province and MSM are major hubs for the spread of the HIV-1 CRF55_01B epidemic in China. A Bayesian Skygrid plot revealed that the effective population size of HIV-1 CRF55_01B experienced increased phase followed by a plateau. All sequences from persons of unknown risk clustered within groups who reported MSM risk. This could be because Chinese MSM may not report such risk due to HIV/AIDS-related stigmatization and discrimination. This study inferred the transmission dynamics of the HIV-1 CRF55_01B epidemic in China at high resolution. The methods developed in this study may be critical for designing effective HIV prevention strategies in China and beyond.