Emergence of genomic diversity and recurrent mutations in SARS-CoV-2

Abstract

SARS-CoV-2 is a SARS-like coronavirus of likely zoonotic origin first identified in December 2019 in Wuhan, the capital of China's Hubei province. The virus has since spread globally, resulting in the currently ongoing COVID-19 pandemic. The first whole genome sequence was published on January 5 2020, and thousands of genomes have been sequenced since this date. This resource allows unprecedented insights into the past demography of SARS-CoV-2 but also monitoring of how the virus is adapting to its novel human host, providing information to direct drug and vaccine design. We curated a dataset of 7666 public genome assemblies and analysed the emergence of genomic diversity over time. Our results are in line with previous estimates and point to all sequences sharing a common ancestor towards the end of 2019, supporting this as the period when SARS-CoV-2 jumped into its human host. Due to extensive transmission, the genetic diversity of the virus in several countries recapitulates a large fraction of its worldwide genetic diversity. We identify regions of the SARS-CoV-2 genome that have remained largely invariant to date, and others that have already accumulated diversity. By focusing on mutations which have emerged independently multiple times (homoplasies), we identify 198 filtered recurrent mutations in the SARS-CoV-2 genome. Nearly 80% of the recurrent mutations produced non-synonymous changes at the protein level, suggesting possible ongoing adaptation of SARS-CoV-2. Three sites in Orf1ab in the regions encoding Nsp6, Nsp11, Nsp13, and one in the Spike protein are characterised by a particularly large number of recurrent mutations (>15 events) which may signpost convergent evolution and are of particular interest in the context of adaptation of SARS-CoV-2 to the human host. We additionally provide an interactive user-friendly web-application to query the alignment of the 7666 SARS-CoV-2 genomes.

Stability of SARS-CoV-2 Phylogenies

“…One possible approach is to mask out specific sites in the genome sequence where recurring errors are suspected, as suggested previously [24] . However, genuine recurrent mutations that may contain important information about properties of viral evolution [6,8,[25][26][27] are sometimes hard to distinguish from recurrent systematic errors, and this could obscure important biology. Here, we present data that we hope will help the community make the important decision as to how to treat potential errors in SARS-CoV-2 genome sequences.…”

“…Extremely rapid whole genome sequencing has enabled nearly real-time tracing of the evolution of the SARS-CoV-2 pandemic [1][2][3][4][5] . By leveraging sequence data produced by labs throughout the world, researchers can trace transmission of the virus across human populations [6][7][8][9][10][11][12][13][14] . Typically, viral evolution is encapsulated by a phylogenetic tree relating all of the virus samples in a large set to one another [5,[15][16][17][18][19] .…”

Emerging phylogenetic structure of the SARS-CoV-2 pandemic

“…The closest relatives (RaTG13 and RmYN02, 96% and 93% nucleotide identity respectively) derive from the Intermediate Horseshoe bat (Rhinolophus affinis) and the Malayan Horseshoe bat (Rhinolophus malayanus) 2 , although the original host is yet to be conclusively identified 3 . Since spilling over to humans, the virus has diverged rapidly, but it is unclear whether these mutations have resulted in SARS-CoV-2 lineages with different epidemiological and evolutionary characteristics [4][5][6][7][8][9] . Several lineages have been highlighted for potential significance [4][5][6]9 .…”

“…Since spilling over to humans, the virus has diverged rapidly, but it is unclear whether these mutations have resulted in SARS-CoV-2 lineages with different epidemiological and evolutionary characteristics [4][5][6][7][8][9] . Several lineages have been highlighted for potential significance [4][5][6]9 . For consistency, we adopt the nomenclature outlined in 8 which classifies the initial lineages as A and B (previously labelled 'S' and 'L' 4 ).…”

“…For example, some lineages within a population can be rapidly expanding whereas others can be stationary 8 . Utilizing large numbers of sequences provided by GISAID 9 and recently developed phylodynamic tools, we interrogate SARS-CoV-2 population patterns to identify 'hidden' structure in the pandemic and investigate whether lineages are geographically partitioned and/or are on distinct demographic trajectories.…”