Phylogenetic network analysis of SARS-CoV-2 genomes
Peter Forster
a,b,c,1
, Lucy Forster
d
, Colin Renfrew
b,1
, and Michael Forster
c,e
a
Institute of Forensic Genetics, 48161 Münster, Germany;
b
McDonald Institute for Archaeological Research, University of Cambridge, Cambridge CB2 3ER,
United Kingdom;
c
Fluxus Technology Limited, Colchester CO3 0NU, United Kingdom;
d
Lakeside Healthcare Group at Cedar House Surgery, St Neots PE19
1BQ, United Kingdom; and
e
Institute of Clinical Molecular Biology, Christian-Albrecht-University of Kiel, 24105 Kiel, Germany
Contributed by Colin Renfrew, March 30, 2020 (sent for review March 17, 2020; reviewed by Toomas Kivisild and Carol Stocking)
In a phylogenetic network analysis of 160 complete human severe
acute respiratory syndrome coronavirus 2 (SARS-Cov-2) genomes,
we find three central variants distinguished by amino acid changes,
which we have named A, B, and C, with A being the ancestral type
according to the bat outgroup coronavirus. The A and C types are
found in significant proportions outside East Asia, that is, in Euro-
peans and Americans. In contra st, the B type is the most common
type in East Asia, and its ancestral genome appears not to have
spread outside East Asia without first mutating into derived B types,
pointing to founder effects or immunological or environmental
resistance against this type outside Asia. The network faithfully
traces routes of infections for documented coronavirus disease
2019 (COVID-19) cases, indicating that phylogenetic networks
can likewise be successfully used to help trace undocumented
COVID-19 infection sources, which can then be quarantined to pre-
vent recurrent spread of the disease worldwide.
SARS-CoV-2 evolution
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subtype
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ancestral type
T
he search for human origins seemed to take a step forward
with the publication of the global human mitochondrial DNA
tree (1). It soon turned out, however, that the tree-building
method did not facilitate an unambiguous interpretation of the
data. This motivated the development, in the early 1990s, of
phylogenetic network methods which are capable of enabling the
visualization of a multitude of optimal trees (2, 3). This network
approach, based on mitochondrial and Y chromosomal data,
allowed us to reconstruct the prehistoric population movements
which colonized the planet (4, 5). The phylogenetic network
approach from 2003 onward then found application in the re-
construction of language prehistory (6). It is now timely to apply
the phylogenetic network approach to virological data to explore
how this method can contribute to an understanding of coronavirus
evolution.
In early March 2020, the GISAID database (https://www.
gisaid.org/) contained a compilation of 253 severe acute re-
spiratory syndrome coronavirus 2 (SARS-CoV-2) complete and
partial genomes contributed by clinicians and researchers from
across the world since December 2019. To understand the evo-
lution of this virus within humans, and to assist in tracing in-
fection pathways and designing preventive strategies, we here
present a phylogenetic network of 160 largely complete SARS-Cov-2
genomes (Fig. 1).
Zhou et al. (7) recently reported a closely related bat coro-
navirus, with 96.2% sequence similarity to the human virus. We
use this bat virus as an outgroup, resulting in the root of the
network being placed in a cluster of lineages which we have la-
beled “A.” Overall, the network, as expected in an ongoing
outbreak, shows ancestral viral genomes existing alongside their
newly mutated daughter genomes.
There are two subclusters of A which are distinguished by the
synonymous mutation T29095C. In the T-allele subcluster, four
Chinese individuals (from the southern coastal Chinese province
of Guangdong) carry the ancestral genome, while three Japanese
and two American patients differ from it by a number of muta-
tions. These American patients are reported to have had a history
of residence in the presumed source of the outbreak in Wuhan.
The C-allele subcluster sports relatively long mutational branches
and includes five individuals from Wuhan, two of which are
represented in the ancestral node, and eight other East Asians
from China and adjacent countries. It is noteworthy that nearly
half (15/33) of the types in this subcluster, however, are found
outside East Asia, mainly in the United States and Australia.
Two derived network nodes are striking in terms of the
number of individuals included in the nodal type and in muta-
tional branches radiating from these nodes. We have labeled
these phylogenetic clusters B and C.
For type B, all but 19 of the 93 type B genomes were sampled
in Wuhan (n = 22), in other parts of eastern China (n = 31), and,
sporadically, in adjacent Asian countries (n = 21). Outside of
East Asia, 10 B-types were found in viral genomes from the
United States and Canada, one in Mexico, four in France, two in
Germany, and one each in Italy and Australia. Node B is derived
from A by two mutations: the synonymous mutation T8782C and
the nonsynonymous mutation C28144T changing a leucine to a
serine. Cluster B is striking with regard to mutational branch
lengths: While the ancestral B type is monopolized (26/26 ge-
nomes) by East Asians, every single (19/19) B-type genome
outside of Asia has evolved mutations. This phenomenon does
not appear to be due to the month-long time lag and concomi-
tant mutation rate acting on the viral genome before it spread
outside of China (Dataset S1, Supplementary Table 2). A com-
plex founder scenario is one possibility, and a different expla-
nation worth considering is that the ancestral Wuhan B-type
virus is immunologically or environmentally adapted to a large
section of the East Asian population, and may need to mutate to
overcome resistance outside East Asia.
Significance
This is a phylogenetic network of SARS-CoV-2 genomes sam-
pled from across the world. These genomes are closely related
and under evolutionary selection in their human hosts, some-
times with parallel evolution events, that is, the same virus
mutation emerges in two different human hosts. This makes
character-based phylogenetic networks the method of choice
for reconstructing their evolutionary paths and their ancestral
genome in the human host. The network method has been
used in around 10,000 phylogenetic studies of diverse organ-
isms, and is mostly known for reconstructing the prehistoric
population movements of humans and for ecological studies,
but is less commonly employed in the field of virology.
Author contributions: P.F. and M.F. performed research; P.F., L.F., and M.F. analyzed data;
P.F. and M.F. performed statistical analyses; P.F., C.R., and M.F. wrote the paper; and C.R.
wrote the Introduction.
Reviewers: T.K., Katholieke Universi teit Leuven; and C.S., Univer sity Medical Center
Hamburg-Eppendorf.
The authors declare no competing interest.
This open access article is distributed under Creative Commons Attribution License 4.0
(CC BY).
1
To whom correspondence may be addressed. Email: pf223@cam.ac.uk or acr10@cam.
ac.uk.
This article contains supporting information online at https://www.pnas.org/lookup/suppl/
doi:10.1073/pnas.2004999117/-/DCSupplemental.
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Type C differs from its parent type B by the nonsynonymous
mutation G26144T which changes a glycine to a valine. In the
dataset, this is the major European type (n = 11), with repre-
sentatives in France, Italy, Sweden, and England, and in California
and Brazil. It is absent in the mainland Chinese sample, but
evident in Singapore (n = 5) and a lso f ound in Hong Kong,
Taiwan, and South Korea.
One practical application of the phylogenetic network is to
reconstruct infection paths where they are unknown and pose a
public health risk. The following cases where the infection his-
tory is well documented may serve as illustrations (SI Appendix ).
On 25 February 2020, the first Brazilian was reported to have
been infected following a visit to Italy, and the network algorithm
reflects this with a mutational link between an Italian and his
Brazilian viral genome in cluster C (SI Appendix, Fig. S1). In
another case, a man from Ontario had traveled from Wuhan in
central China to Guangdong in southern China and then
returned to Canada, where he fell ill and was conclusively di-
agnosed with coronavirus disease 2019 (COVID-19) on 27 January
2020. In the phylogenetic network (SI Appendix,Fig.S2), his virus
genome branches from a reconstructed ancestral node, with derived
virus variants in Foshan and Shenzhen (both in Guangdong
province), in agreement with his travel history. His virus genome
now coexists with those of other infected North Americans (one
Canadian and two Californians) who evidently share a common
viral genealogy. The case of the single Mexican viral genome in
the network is a documented infection diagnosed on 28 February
2020 in a Mexican traveler to Italy. Not only does the network
confirm the Italian origin of the Mexican virus (SI Appendix,Fig.
S3), but it also implies that this Italian virus derives from the first
documented German infection on 27 January 2020 in an em-
ployee working for the Webasto company in Munich, who, in turn,
had contracted the infection from a Chinese colleague in Shang-
hai who had received a visit by her parents from Wuhan. This viral
journey from Wuhan to Mexico, lasting a month, is documented
by 10 mutations in the phylogenetic network.
This viral network is a snapshot of the early stages of an epi-
demic before the phylogeny becomes obscured by subsequent
migration and mutation. The question may be asked whether the
rooting of the viral evolution can be achieved at this early stage
by using the oldest available sampled genome as a root. As SI
Appendix, Fig. S4 shows, however, the first virus genome that was
sampled on 24 December 2019 already is distant from the root
type according to the bat coronavirus outgroup rooting.
Geography
BAT
CHINA
EAST ASIA
USA
CANADA
EUROPE
AUSTRALIA
MEXICO
BRAZIL
C
B
A
BAT
Fig. 1. Phylogenetic network of 160 SARS-CoV-2 genomes. Node A is the root cluster obtained with the bat (R. affinis) coronavirus isolate BatCoVRaTG13
from Yunnan Province. Circle areas are proportional to the number of taxa, and each notch on the links represents a mutated nucleotide position. The
sequence range under consideration is 56 to 29,797, with nucleotide position (np) numbering according to the Wuhan 1 reference sequence (8). The median-
joining network algorithm (2) and the Steiner algorithm (9) were used, both implemented in the software package Network5011CS (https://www.fluxus-
engineering.com/), with the parameter epsilon set to zero, gener ating this network containing 288 most-parsimonious trees of length 229 mutations. The
reticulations are mainly caused by recurrent mutations at np11083. The 161 taxa (160 human viruses and one bat virus) yield 101 distinct genomic sequences.
The phylogenetic diagram is available for detailed scrutiny in A0 poster format (SI Appendix, Fig. S5) and in the free Network download files.
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The described core mutations have been confirmed by a va-
riety of contributing laboratories and sequencing platforms and
can be considered reliable. The phylogeographic patterns in the
network are potentially affected by distinctive migratory histo-
ries, founder events, and sample size. Nevertheless, it would be
prudent to consider the possibility that mutational variants might
modulate the clinical presentation and spread of the disease. The
phylogenetic classification provided here may be used to rule out
or confirm such effects when evaluating clinical and epidemio-
logical outcomes of SARS-CoV-2 infection, and when designing
treatment and, eventually, vaccines.
Materials and Methods
The Global Initiative on Sharing Avian Influenza Data (GISAID) was founded
in 2006, and, since 2010, has been hosted by the German Federal Ministry of
Food, Agriculture and Consumer Protection. GISAID has also become a
coronavirus repository since December 2019. As of 4 March 2020, the cutoff
point for our phylogenetic analysis, the GISAID database (https://www.gisaid.
org/) had compiled 254 coronavirus genomes, isolated from 244 humans,
nine Chinese pangolins, and one bat Rhinolophus affinis (BatCoVRaTG13
from Yunnan Province, China). The sequences have been deposited by 82
laboratories listed in Dataset S1, Supplementary Table 1. Although SARS-CoV-2
is an RNA virus, the deposited sequences, by convention, are in DNA format.
Our initial alignment confirmed an earlier report by Zhou et al. (7) that the
pangolin coronavirus sequences are poorly conserved with respect to the hu-
man SARS-CoV-2 virus, while the bat coronavirus yielded a sequence similarity
of 96.2% in our analysis, in agreement with the 96.2% published by Zhou et al.
We discarded partial sequences, and used only the most complete genomes
that we aligned to the full reference genome by Wu et al. (8) comprising
29,903 nucleotides. Finally, to ensure comparability, we truncated the flanks of
all sequences to the consensus range 56 to 29,797, with nucleotide position
numbering according to the Wuhan 1 reference sequence (8). The laboratory
codes of the resulting 160 sequences and the bat coronavirus sequences are
listed in Dataset S1, Supplementary Table 2 (Coronavirus Isolate Labels).
The 160 human coronavirus sequences comprised exactly 100 different
types. We added to the data the bat coronavirus as an outgroup to determine
the root within the phylogeny. Phylogenetic network analyses were per-
formed with the Network 5011CS pack age, which includes, among other
algorithms, the median joining network algorithm (3) and a Steiner tree
algorithm to identify most-parsimonious trees within complex networks (9).
We coded gaps of adjacent nucleotides as single deletion events (these
deletions being rare, up to 24 nucleotides long, and mostly in the amino acid
reading frame) and ran the data with the epsilon parameter set to zero, and
performed an exploratory run by setting the epsilon parameter to 10. Both
settings yielded a low-complexity network. The Steiner tree algorithm was
then run on both networks and provided the identical result that the most-
parsimonious trees within the network were of length 229 mutations. The
structures of both networks were very similar, with the epsilon 10 setting
providing an additional rectangle between the A and B clusters. The net-
work output was annotated using the Network Publisher option to indicate
geographic regions, sample collection times, and cluster nomenclature.
Data Availability. The nucleotide sequences of the SARS-CoV-2 genomes used
in this analysis are available, upon free registration, from the GISAID data-
base (https://www.gisaid.org/). The Network5011 software package and
coronavirus network files are available as shareware on the Fluxus
Technology website (https://www.fluxus-engineering.com/).
ACKNOWLEDGMENTS. We gratefully acknowledge the authors and origi-
nating and submitting laboratories of the sequences from GISAID’s EpiFlu(TM)
Database on which this research is based. We are grateful to Trevor Bedford
(GISAID) for providing instructions and advice on the database. A table of the
contributors is available in Dataset S1, Supplementary Table 1. We thank Arne
Röhl for assessing the network.
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