New framework for recombination and adaptive evolution analysis with application to the novel coronavirus SARS-CoV-2

Author:

Wang Yinghan1,Zeng Jinfeng1,Zhang Chi1,Chen Cai1,Qiu Zekai1,Pang Jiali2,Xu Yutian3,Dong Zhiqi1,Song Yanxin4,Liu Weiying1,Dong Peipei1,Sun Litao1,Chen Yao-Qing1,Shu Yuelong15,Du Xiangjun15

Affiliation:

1. School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China

2. School of Life Sciences, Sun Yat-sen University, Guangzhou, China

3. School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China

4. Lingnan College, Sun Yat-sen University, Guangzhou, China

5. Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, China

Abstract

Abstract The 2019 novel coronavirus (SARS-CoV-2) has spread rapidly worldwide and was declared a pandemic by the WHO in March 2020. The evolution of SARS-CoV-2, either in its natural reservoir or in the human population, is still unclear, but this knowledge is essential for effective prevention and control. We propose a new framework to systematically identify recombination events, excluding those due to noise and convergent evolution. We found that several recombination events occurred for SARS-CoV-2 before its transfer to humans, including a more recent recombination event in the receptor-binding domain. We also constructed a probabilistic mutation network to explore the diversity and evolution of SARS-CoV-2 after human infection. Clustering results show that the novel coronavirus has diverged into several clusters that cocirculate over time in various regions and that several mutations across the genome are fixed during transmission throughout the human population, including D614G in the S gene and two accompanied mutations in ORF1ab. Together, these findings suggest that SARS-CoV-2 experienced a complicated evolution process in the natural environment and point to its continuous adaptation to humans. The new framework proposed in this study can help our understanding of and response to other emerging pathogens.

Funder

Guangdong Frontier and Key Tech Innovation Program

National Key Research and Development Program of China

Shenzhen Science and Technology Program

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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