Genomic epidemiology of SARS-CoV-2 in Guangdong Province, China

Jing Lu; Louis du Plessis; Zhe Liu; Verity Hill; Min Kang; Huifang Lin; Jiufeng Sun; Sarah Francois; Moritz U G Kraemer; Nuno R Faria; John T McCrone; Jinju Peng; Qianling Xiong; Runyu Yuan; Lilian Zeng; Pingping Zhou; Chuming Liang; Lina Yi; Jun Liu; Jianpeng Xiao; Jianxiong Hu; Tao Liu; Wenjun Ma; Wei Li; Juan Su; Huanying Zheng; Bo Peng; Shisong Fang; Wenzhe Su; Kuibiao Li; Ruilin Sun; Ru Bai; Xi Tang; Minfeng Liang; Josh Quick; Tie Song; Andrew Rambaut; Nick Loman; Jayna Raghwani; Oliver Pybus; Changwen Ke

The results also suggest that early phylogenetic analyses of the pandemic should be interpreted carefully. The number of mutations that define phylogenetic lineages are small (often one), and may be similar to the number of sequence differences arising from errors introduced during reverse transcription, PCR amplification, or sequencing. Bayesian estimates of divergence times (Rannala and Yang, 1996) , such as the tMRCA of the pandemic, are based on aggregate numbers of mutations and are expected to be more robust. Further, the low and variable sampling of COVID-19 cases among different regions makes it challenging to evaluate phylogenetic clusters that comprise cases from a single region; although such clusters could indeed represent local transmission, our results show they can also include multiple introductions from a genomically-undersampled location. Therefore, as with all phylogenetic analyses, the SARS-CoV-2 genomes must be interpreted in the context of all available epidemiological information. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.