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\begin{document}

\title{Phylogeography and evolutionary dynamics analysis of porcine
delta-coronavirus with host expansion to humans}



\author[1]{Gen Li}%
\author[2]{Shao-Lun Zhai}%
\author[1]{Xia Zhou}%
\author[1]{Tianbao Chen}%
\author[1]{Jiawei Niu}%
\author[1]{YS Xie}%
\author[1]{Guangbin Si}%
\author[3]{Feng Cong}%
\author[1]{Ruiai Chen}%
\author[1]{Dongsheng He}%
\affil[1]{South China Agricultural University College of Veterinary Medicine}%
\affil[2]{Institute of Animal Health Guangdong Academy of Agricultural Sciences Scientific Observation and Experiment Station of Veterinary Drugs and Diagnostic Techniques of Guangdong Province Ministry of Agriculture of Rural Affairs and Key Laboratory of Animal Disease Prevention of Guangdong Province Guangzhou 510640 China}%
\affil[3]{Guangdong Laboratory Animals Monitoring Institute and Guangdong Provincial Key Laboratory of Laboratory Animals Guangzhou 510633 China}%


\vspace{-1em}



  
  \date{May 26, 2024}


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\selectlanguage{english}
\begin{abstract}
From 2003 onwards, three pandemics have been caused by coronaviruses:
severe acute respiratory syndrome coronavirus (SARS-CoV); middle east
respiratory syndrome coronavirus (MERS-CoV); and, most recently,
SARS-CoV-2. Notably, all three were transmitted from animals to humans.
This would suggest that animals are potential sources of epidemics for
humans. The emerging porcine delta-coronavirus was reported to infect
children. This is a red flag that marks the ability of PDCoV to break
barriers of cross-species transmission to humans. Therefore, we
conducted molecular genetic analysis of global clade PDCoV to
characterize spatio-temporal patterns of viral diffusion and genetic
diversity. PDCoV was classified into three major lineages, according to
distribution and phylogenetic analysis of PDCoV. It can be determined
that PDCoV originated in Asia---most likely in Southeast Asia---through
inference of migration rate and transmission routes. We also selected
six special spike amino acid sequences to align and analyze to find
seven significant mutation sites. The accumulation of these mutations
may enhance dynamic movements, accelerating spike protein membrane
fusion events and transmission. Altogether, our study offers a novel
insight into the diversification, evolution, and interspecies
transmission and origin of PDCoV and emphasizes the need to study the
zoonotic potential of the PDCoV and comprehensive surveillance and
enhanced biosecurity precautions for PDCoV.%
\end{abstract}%



\sloppy


\textbf{1 Introduction}

Coronaviruses (CoVs) are positive-stranded and single-stranded RNA
viruses with an envelope, which belong to members of the order
\emph{Nidomiformes} , family\emph{coronaviridae} and have the largest
genomes, from 25kb to 32kb, among known RNA viruses (Weiss \&
Navas-Martin, 2005). CoVs were the first to isolate in 1937 from the
chicken and had the ability of cross-species transmission. It can infect
birds and mammals, including humans, and mainly cause respiratory and
digestive tract symptoms (Weiss \& Navas-Martin, 2005). Since the
outbreak of SARS in 2003, new coronaviruses continue to be discovered.
MERS-CoV has been reported in recent years. SARS-CoV-2 is still sweeping
the globe now (Gates, 2020; Lancet, 2013; Li, Niu, Fan, Chen, \& He,
2021; Stadler et al., 2003). As of 13 August 2021, there have been
205,338,159 confirmed cases of COVID-19, including 4,333,094 deaths,
reported to the WHO (https://covid19.who.int/). Current research
suggests that SARS-CoV-2 may have originated from bats or pangolins
(Xiao et al., 2020; Zhou et al., 2020).

The emerging porcine delta-coronavirus was first identified in swine
specimens collected from 2011 to 2012 in Hong Kong (Woo et al., 2012).
In 2014, a severe diarrhea outbreak occurred on a US pig farm, suspected
of PEDV infection. However, PDCoV was detected in the feces of pigs
instead of PEDV. Subsequently, PDCoV was detected in Korea, Canada,
India, Thailand, and mainland China (Ajayi et al., 2018; Hu et al.,
2015; Lee et al., 2016; Lorsirigool et al., 2017), posing a significant
threat to the swine industry.

In 2017, Woo found PDCoV may be able to cause respiratory infections in
pigs and that in addition to fecal-oral transmission, the virus could
possibly spread through the respiratory route (Woo et al., 2017). In
2019, specific pathogen-free (SPF) chickens were inoculated with PDCoV
and showed mild diarrhea symptoms and low fecal viral RNA shedding
(Liang et al., 2019). From May 2014 to December 2015, Lednicky collected
a total of 369 samples from children presenting to the school clinic
with acute undifferentiated febrile illness in Ayiti and found three of
them were infected with coronavirus strains, which clustered with PDCoV
(Lednicky et al., 2021). Therefore, PDCoV represented significant
potential in cross-species transmission and spread in new host
populations, implying their potential threat to human health.

To dig into the origin, evolution and transmission of PDCoV, phylogenic
analysis was used to analyze full genome and S gene sequences of PDCoV
to examine source population, time of origin, evolutionary rate, amino
acid sites and potential dissemination routes. The data in the study
will help to formulate countermeasures to deal with the possible future
risk of zoonotic transmission of PDCoV to humans.

\textbf{2 Materials and methods}

2.1 Sample collection and virus isolation

A total of 314 rectal swabs were collected from eight intensive pig
farm, located in Guangdong Province, China between 2017 and 2019. PDCoV
isolation was performed using LLC porcine kidney (LLC-PK) cell line. The
optimal cell culture conditions to isolate and propagate PDCoV in LLC-PK
required Dulbecco's modified eagle medium (DMEM, Gibco, USA),
supplemented with 10\% (v/v) fetal bovine serum (FBS, Gibco), and
10 \selectlanguage{greek}μ\selectlanguage{english}g/mL of trypsin (Chen et al., 2016; Hu et al., 2015; Jung, Miyazaki,
Hu, \& Saif, 2018). The result of isolation was confirmed by an indirect
immunofluorescence assay (ELISA) and reverse transcription-polymerase
chain reaction (RT-PCR) (Supplementary Tables S1).

2.2 Virus extraction and complete gene sequencing

Viral RNA was extracted from 200 \selectlanguage{greek}μ\selectlanguage{english}L of sample using TRIzol reagent
(TaKaRa Biotechnology, Dalian, China) according to the manufacturer's
instructions, and nucleic acids were finally eluted in 30 \selectlanguage{greek}μ\selectlanguage{english}L of the
RNase free H\textsubscript{2}O. Viral genomic RNA was immediately used
for PCR or stored at -80 \selectlanguage{ngerman}°C until use. In total, 15 pairs were designed
for PCR reactions to sequence the PDCoV genomes (Supplementary Tables
S2). Positive plasmids of PDCoV were extracted using a Plasmid Mini Kit
I (200) (Omega Bio-tek, Norcross, GA, USA). Then the positive plasmids
of PDCoV were sequenced by Sangon Biotech (Shanghai, China) Co., Ltd.

2.3 Sequence analysis and model test

We accessed all available PDCoV genomes sequences up to June 2021 from
NCBI GenBank (https://www.ncbi.nlm.nih.gov/). A total of 130 PDCoV
genomes (Supplementary Tables S3)---two of which were sequenced by our
laboratory---and~130 spike genes~sequences, were retrieved by PhyloSuite
(version 1.2.2) to attain no identical sequences (Chen et al., 2016; Hu
et al., 2015; Jung, Miyazaki, Hu, \& Saif, 2018). These PDCoV genomes
sequences were input to MAFFT (multiple sequence alignment based on fast
Fourier transform) to align (Katoh, Kuma, Toh, \& Miyata, 2005; Katoh,
Misawa, Kuma, \& Miyata, 2002). Then aligned sequences were input to
Gblocks to determine the conserved domains and edited manually (Talavera
\& Castresana, 2007). The best fit nucleotide substitution models were
tested by ModelFinder (version 1.6.8) (Kalyaanamoorthy, Minh, Wong, von
Haeseler, \& Jermiin, 2017).

2.4 Maximum-likelihood and Bayesian Inference analysis of the PDCoV

The best fit general time reversible substitution model with an
empirical base frequencies and relaxing gamma distributed rate
heterogeneity (GTR+F+R5) with 1000 bootstraps for Maximum-likelihood
(ML) trees of PDCoV genomes was constructed by IQ-RTEE (version 1.6.8)
according to corrected Akaike information criterion (AICc) (Minh et al.,
2020).

The best fit general time reversible substitution model with a
proportion of invariant sites, empirical base frequencies and gamma
distributed rate heterogeneity (GTR+F+I+G4) with 2000000 generations for
Bayesian Inference (BI) trees of PDCoV genomes was input to MrBayes
(version 3.2.6) according to corrected Akaike Information Criterion
(AICc) (Huelsenbeck \& Ronquist, 2001; Ronquist et al., 2012; Ronquist
\& Huelsenbeck, 2003).

The final results were illustrated in the Interactive Tree of Life
(iTOL, https://itol.embl.de/) (Letunic \& Bork, 2007; 2021).

2.5 Phylogenetic analysis of spike gene

Bayesian evolutionary analysis by sampling trees (BEAST) package was
used to estimate the time to the most recent common ancestor (tMRCA) and
evolutionary rates. A total of 130 spike genes~sequences were selected
from 130 PDCoV genomes and input to IQ-TREE to reconstruct the ML tree.
Then we used TempEst (version 1.5.3) to ensure that these sequences had
sufficient temporal symbol (Rambaut, Lam, Max Carvalho, \& Pybus, 2016).
According to the ModelFinder (version 1.6.8) result for BEAST (version
1.10.4), the Bayesian Markov chain Monte Carlo (MCMC) method implemented
in the BEAST (BEAST, version 1.10.4) package and BEAGLE was used (Ayres
et al., 2012; Suchard \& Rambaut, 2009), with the GTR+G nucleotide
substitution model, a strict molecular clock model and the Coalescent
Bayesian Skyline tree prior (Drummond, Rambaut, Shapiro, \& Pybus, 2005;
Ferreira \& Suchard, 2008). The chain length was 500000000 with a
sampling frequency every 50000 steps. Tracer software (version 1.7) was
used to test that all parameter estimates yielded effective sampling
size \textgreater{}200 and burning up the period of 10\% of the total
chain length (Rambaut, Drummond, Xie, Baele, \& Suchard, 2018). The
final Bayesian maximum clade credibility (MCC) tree was generated by
TreeAnnotator (version 2.6.3) (http://beast.community/treeannotator) and
illustrated in Figtree (version 1.4.3)
(http://tree.bio.ed.ac.uk/software/figtree/). Then, to estimate the
population dynamics of PDCoV, Bayesian Skyline Plot was used to
reconstruct the population history. The results were shown by analysis
of Bayesian Skyline Reconstruction in Tracer (version 1.7)
(Barido-Sottani et al., 2018).

2.6 Phylogeographic inference

To estimate phylogenies and divergence times and explore phylogeography,
the same preprocessing as 2.5 on a total of 130 spike genes~sequences
were input to BEAST (version 1.10.4) package, with the GTR+G nucleotide
substitution model, an uncorrelated relaxed molecular clock model and
the BSSVS (Bayesian Stochastic Search Variable Selection) traits model
(Barido-Sottani et al., 2018)(Li \& Drummond, 2012; Su et al., 2015),
according to the results from path sampling and stepping-stone sampling
(Supplementary Tables S4)(Lartillot \& Philippe, 2006). The chain length
was 500000000 with a sampling frequency every 50000 steps. Tracer
software (version 1.7) was used to test that all parameter estimates
yielded effective sampling size \textgreater{}200 and burning the period
of 10\% of the total chain length. The trees were generated by
TreeAnnotator (version 2.6.3) (http://beast.community/treeannotator) and
illustrated in Figtree (version 1.4.3)
(http://tree.bio.ed.ac.uk/software/figtree/). The phylogeography results
were analyzed by Spatial Phylogenetic Reconstruction of Evolutionary
Dynamics (SPREAD3, version 0.9.7) (Bielejec, Rambaut, Suchard, \& Lemey,
2011).

2.7 Analysis of spike protein

According to the features of PDCoV from GenBank, Illustrator for
Biological Sequences (IBS, version 1.0.3) was used to visualize
protein\selectlanguage{english}-encoding segments in PDCoV (Liu et al., 2015). Amino acid
sequences of spike protein were input to SWISS-MODEL to find proper
models and illustrated by Visual Molecular Dynamics (VMD, version 1.9.4)
(http://www.ks.uiuc.edu/) (Waterhouse et al., 2018). BioAider (version
1.334) was used to analyze mutation of these protein sequences (Zhou,
Qiu, Pu, Huang, \& Ge, 2020).

\textbf{3 Results}

3.1 Detection and isolation of PDCoV

There was a total of 42 positive samples for PDCoV in 314 samples, which
were suspected of PDCoV, with a positive rate of 13.4\%. Two PDCoV
completed genome were obtained in this study, whose accessions were
MH715491 and MT263013 in GenBank. Moreover, a strain of PDCoV
(MT263013), which could be stably passaged on the LLC-PK cell line, was
successfully isolated and confirmed by an indirect immunofluorescence
assay (ELISA) and reverse transcription-polymerase chain reaction
(RT-PCR) (Fig. 1).

3.2 Distribution and phylogenetic analysis of PDCoV

In 2012, PDCoV was first found in Hong Kong, China, and broke out in the
United States in 2014. At present, PDCoV has been reported in more than
11 countries all over the world. In China, pig farms in 14 provinces
were infected with PDCoV (Fig. 2). It has spread all over the world,
showing a global trend. The analysis results from the ML tree and BI
tree for PDCoV completed genome were almost identical (Fig. 3).~The
results indicated that the full genomes would be classified into three
major lineages, which named the Southeast Asia (SEA) lineage, including
Thailand, Vietnam and Laos, America lineage, including the USA, Peru,
Japan, and South Korea (JSK), and China (CHN) lineage. We also observed
that MW685622 and MW685624 in Ayiti were highly similar to KY065120 in
Tianjin, China (99.8\%) and MW685623 in Ayiti were highly similar to
KR150443 in Arkansas, USA (98.9\%).

Bayesian Skyline Plot analysis revealed that the estimated effective
population size went up from 15 to 45 between 1989 and 2010, after a
brief fluctuation, and the effective population floated in a range of
around 70 up to 2019 (Fig. 4a).

According to the root-to-tip regression from TempEst (version 1.5.3),
the analysis of temporal structure revealed aspects of the clock-like
structure of spike gene (n\selectlanguage{english} =\selectlanguage{english} 130, correlation coefficient = 0.56,
R\textsuperscript{2} = 0.32), which indicated the sufficiently strong
temporal signal to estimate time-calibrated phylogenies using molecular
clock models (Supplementary Figs S1). Similar to the full genome, spike
genes were also classified into three major lineages by the analysis of
maximum clade credibility (MCC) trees (Fig. 4b). Moreover, our
reconstruction confirmed that the virus spread from the CHN lineage,
however, it was interesting that SEA lineage was the origin according
the BSSVS analysis. The MCC tree indicated that the probability for
PDCoV originating from the CHN lineage (49.05\%) and SEA lineage
(48.45\%) is similar. BSSVS analysis demonstrated PDCoV spread from
Southeast Asia to the USA, Ayiti, Peru and China with high BF value and
posterior probability (Fig. 5a, Supplementary Tables S5) and spread from
China with low BF value and posterior probability. Combining these two
points, it can be determined that PDCoV originated in Asia, more likely
in Southeast Asia, as consistent with the results of Xiao's phylogenetic
analysis (Ye et al., 2020).

The phylogeographic inference indicated that PDCoV might have originated
around June of 1989 (June 1982--January 1996, 95\% highest posterior
density).

3.3 The spread of PDCoV

The worldwide spatial dispersal networks of PDCoV were reconstructed. We
selected the transmission routes with BF values exceeding 3 and
posterior probability exceeding 0.5 to analyze (Ye et al., 2020). There
were six discrete sampling locations and nine significant transmission
routes (Fig. 6). SEA and JSK were the major output of PDCoV. SEA was
linked with four locations, including Ayiti (BF = 68.10, migration rate
= 0.924), JSK (BF = 9.48, migration rate = 0.938), the USA (BF = 6.97,
migration rate = 0.936), and China (BF = 38425, migration rate = 1.345).
JSK had connections to four locations, including Peru (BF = 54.13,
migration rate = 0.913), USA (BF = 4.62, migration rate = 0.927), SEA
(BF = 9.93, migration rate = 0.958) and Ayiti (BF = 70.21, migration
rate = 0.933). In addition, there was a transmission routes from the USA
to JSK (BF = 7.52, migration rate = 3.553) (Fig. 5b, Supplementary
Tables S5). China and Southeast Asia are adjacent to each other, the
distance is about 2000km and the communication is relatively close.
Therefore, there was the highest BF value and high migration rate.
Remarkably, a special case got our attention. We observed that a strong
signal of viral dissemination from the USA to JSK, even though the two
places are approximately 11200\selectlanguage{english} km apart, suggesting that the PDCoV in
the JSK may spread from the USA, as consistent with the results of MCC
tree. In Ayiti, pigs were reintroduced from North American populations,
mainly the USA and in small part, Canada (Alexander, 1992) and there was
a certain link between Ayiti and JSK. Infections in Ayiti were likely to
be associated with the importation of pigs from the USA.

3.4 Protein structure analysis

Two samples named LC216914 and LC216915 in GenBank were collected from
pigs' nasopharyngeal, suggesting PDCoV may be able to cause respiratory
infections in pigs (Woo et al., 2017). A sample named MK248485 in
GenBank was collected from chickens, suggesting PDCoV can infect
chickens (Boley et al., 2020). Three samples named MW685622, MW685623,
and MW685624 in GenBank were collected from children's blood, suggesting
PDCoV has the potential to infect humans (Lednicky et al., 2021).
Comparing the six special sequences with all the sequences, it was found
that there were similar changes in seven amino acid sites. The structure
of the S protein from residues 52 to 1017 was shown in Fig. 7, because
this region of beginning and end are hydrophobic and can adversely
affect protein solubility (Lednicky et al., 2021).

Residue 38 was mutated from P to L, which may affect the secondary
structure of the protein, because proline is a subamino acid, which
cannot form intra-chain hydrogen bonds and is prone to \selectlanguage{greek}β-\selectlanguage{english}turn angle
formation. Residue 40 was mutated from R to S, which reduces the space
resistance and enhances hydrophilicity. There was a N-glycosylation site
between residue 41 and 44 so residue deletion at site 45 may affect
glycosylation (Lednicky et al., 2021). The mutation between A and V at
residue 137 and 551 may eliminates specific Van der Waals contact,
potentially enhancing protein flexibility and dynamic movement of S1.
Moreover, this change may represent a common mechanism that enhances
dynamic movements, accelerating virus membrane fusion events and
transmission (Lednicky et al., 2021; Thompson et al., 2021). Mutation at
residue 670 altered the spatial site resistance. The phosphorylation of
the protein is mainly carried out on tyrosine, serine, and threonine
residues in the peptide chain. Residue 689 was mutated from S to A, with
a phosphorylation site losing (Fig. 8 and Table. 1).

\textbf{4 Discussion}

The outbreak of COVID-19 has raised great concern all over the world and
poses serious threat to global public health. Therefore, Covs gained
increasing attention. When researchers examined blood samples from Ayiti
children in early 2021, three samples were found to be infected with
PDCoV (Lednicky et al., 2021). Of note, PDCoV has repeatedly crossed the
host barrier to chicken (Boley et al., 2020; Liang et al., 2019). This
phenomenon exhibits the same cross-species transmission as SARS-COV-2,
which suggested that the emerging porcine delta-coronavirus may be a
potential threat to human health. Here, we adopted a phylogeographic
approach to examine the time of origin, evolutionary rate,
diversification patterns and potential transmission routes of PDCoV and
selected six special spike amino acid sequences to align and analyze.

PDCoV is an emerging coronavirus causing severe enteritis, diarrhea, and
vomiting in piglets. PDCoV was first discovered in Hong Kong, China in
2012, but began to spread in the United States in 2014. Now many
countries in the world have reported that pigs were infected with PDCoV.
We attained 42 positive samples for PDCoV from eight intensive pig
farms, located in Guangdong Province, China and sequenced two PDCoV
completed genomes. Moreover, a strain of PDCoV, which could be stably
passaged on the LLC-PK cell line was successfully isolated. According to
phylogenetic analysis of PDCoV, our findings indicated that PDCoV would
be classified into three major lineages: China lineage; USA lineage; and
Southeast Asia lineage. There were three PDCoV in Ayiti that can infect
children, two of which were highly similar to KY065120 in Tianjin, China
(99.8\%), and the rest were highly similar to KR150443 in Arkansas, USA
(98.9\%). However, after suffering from African swine fever in Ayiti,
pigs were reintroduced mainly from American populations. The worldwide
spatial dispersal networks of PDCoV also indicated the US lineage was
one of the origins to Ayiti. Therefore, PDCoV infected in Ayiti was most
likely from America (Alexander, 1992; Lednicky et al., 2021).

The MCC tree showed that PDCoV originated in Asia, between China and
southeast Asia, and more likely in Southeast Asia in 1989. In addition,
according to Bayesian Skyline Plot analysis, effective population size
of PDCoV tended to level off and stabilize at around 70. We observed the
association between geographic distance and migration rate to clarify
space dynamics. However, we observed a strong signal of viral
dissemination (migration rate = 3.55) from US to Japan and South Korea,
with a long distance (about 11200 km). This showed there was no certain
connection between geographic distance and migration rate. Moreover, the
scatter plot of distance and migration rate also did not display a
certain trend (Supplementary Tables S6, Fig S2). It may be due to the
swine trade between countries and artificial or feed contamination that
affects the rate of natural transmission.

To analyse the effect of amino acid mutation on cross-species
transmission, we found six PDCoV sequences that can spread across
species, and align the amino acids of their spike protein. By analyzing
the amino acid sequence of spike protein, seven significant mutation
sites were defined. The accumulation of these mutations may enhance
dynamic movements, accelerating virus membrane fusion events and
transmission.

Frankly, this study has several limitations. First, sampling bias, no
same number of samples in different regions, may have affected the
Bayesian phylogenic reconstruction and inference of the transmission
networks (Alexander, 1992; Lednicky et al., 2021). Second, the
information from sequences contains the most regions infected with PDCoV
but does not cover all regions, because there are some places infected
with PDCoV, but no sequence uploaded in GenBank.

In summary, our findings offer novel insights into the diversification,
evolution, and interspecies transmission and origin of PDCoV. We also
briefly analyzed why humans are infected with PDCoV. Increasing evidence
strongly implicates that CoVs have a high capacity for cross-species
transmission. Given that pigs are in frequent contact with humans and
wild animals, the lower interspecies hurdles in pigs would make them a
potential mixing vessel for CoVs (Ye et al., 2020). Therefore,
comprehensive surveillance and enhanced biosecurity precautions for
PDCoV should be taken to prevent further pandemic such as COVID-19.

\section*{Declaration of Competing
Interest}

{\label{declaration-of-competing-interest}}

The authors state that they have no competing interests

\section*{Acknowledgments}

{\label{acknowledgments}}

This work was supported by Key Laboratory of Zoonosis Prevention and
Control of Guangdong Province, the Guangdong Province Pig Industrial
System Innovation Team (Grant Number 2018LM1103).

\section*{Ethical Approval}

{\label{ethical-approval}}

Ethical statement is not applicable in this study. The sampling and data
publication were approved by the owners of animal. Animals were humanly
treated during samples collected.

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\textbf{Fig.1 Isolation and identification of PDCoV}

(a) The samples were tested by RT-PCR to determine that the samples were
infected with PDCoV and no other common virus were present. (b)
Isolation and passage of PDCoV in LLC-PK cells. Magnification: 200\selectlanguage{ngerman}×. (c)
Indirect immunofluorescence assay on LLC-PK cells infected with PDCoV.
(d) Indirect immunofluorescence assay on the intestine of PDCoV-infected
pigs. The primary antibody is a monoclonal antibody against N protein.

\textbf{Fig. 2 Geographical distribution of PDCoV around the world and
in China}

(a) Different countries are denoted by different colors; (b) Different
provinces in China are denoted by different colors.

\textbf{Fig. 3 Maximum-likelihood tree and bayesian inference tree}

(a) ML tree of completed PDCoV gene. (b) BI tree of completed PDCoV
gene. Different colors represent different regions. Japan and South
Korea, JSK. Southeast Asia, SEA. USA, the Unite States America.

\textbf{Fig. 4 Demographic history of PDCoV spike gene}

(a) Demographic history was inferred by bayesian skyline analysis. The
median and 95\% HPD intervals were plotted. (b) A MCC tree of the S gene
sampled in nine different countries. PDCoV were classified into three
major lineages. The pie charts indicate the probability of chosen nodes.
Except for the four chosen nodes shown, the probability of the rest of
the nodes is greater than 90\%, so they are not shown.

\textbf{Fig. 5 BF supports and migration rate for each transmission
routes}

(a) Sufficient signal transmission routes were shown. (b) Migration
rates were indicated for each support transition routes. (c) The
migration changes of PDCoV in each region were exhibited.

\textbf{Fig. 6 Spatial diffusion of PDCoV}

The spatial diffusion of PDCoV was determined by Bayesian phylogeography
inference of spike gene sequences. Curves show the among-country virus
lineage transitions statistically supported with BF \textgreater{}3 and
posterior probability \textgreater{}0.5 for PDCoV. Widths and colors of
the curve represent migration rate and BF support, respectively.

\textbf{Fig. 7 Visualization of PDCoV structure}

(a) Overall structure of PDCoV contains two large ORF (opening reading
frame), four structural proteins and tree accessory proteins. (b)
Structure of spike protein is classified into three parts, S1-NTD
(N-terminal domain), S1-CTD (C-terminal domain) and S2(Shang et al.,
2018).

\textbf{Fig. 8 Three-dimensional view of S protein}

The five selected amino acids were marked in red and the locations
indicated by arrows. The other mutations (position 38, 40 and 50) were
not resolved in the structure.\selectlanguage{english}
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