Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia

Frontiers in Public Health

article

Mingjian Zhu¹  Natthjija Latthitham²  Lanjuan Li¹  Jian Shen¹  Qianli Zeng³  Joanna Weihui Tan⁴  Jirapat Kleepbua²  Ian Chew¹  Jia Xian Law⁵  Sien Ping Chew⁶  Anita Tangathajinda² 

[1] State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine;Thammasat University Hospital;Shanghai Institute of Biological Products;Faculty of Arts and Social Sciences, National University of Singapore;Tuanku Ja'afar Hospital;Shanghai Jiao Tong University School of Medicine

关键词: SARS-CoV-2;    phylogenetic tree;    phylogeography;    phylodynamics;    effective population size (Ne);    Bayesian inference;    Southeast Asia;   

DOI  :  10.3389/fpubh.2021.685315

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region. Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model. Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10 −3 (1.292 × 10 −3 to 1.613 × 10 −3 ) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia. Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.

【 授权许可】

CC BY