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Are pangolins the intermediate host of the 2019 novel coronavirus (2019-nCoV) ?

Ping Liu1*, Jing-Zhe Jiang2*, Xiu-Feng Wan3,4,5,6,7, Yan Hua8, Xiaohu Wang9, Fanghui

Hou10, Jing Chen9, Jiejian Zou10, Jinping Chen1†

1
Guangdong Key Laboratory of Animal Conservation and Resource Utilization,

Guangdong Public Laboratory of Wild Animal Conservation and Utilization,

Guangdong Institute of Applied Biological Resources, Guangzhou, Guangdong

Province 510260, China. 2Key Laboratory of South China Sea Fishery Resources

Exploitation & Utilization, Ministry of Agriculture, South China Sea Fisheries

Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, Guangdong

Province 510300, China. 3Department of Molecular Microbiology and Immunology,

School of Medicine, University of Missouri, Columbia, MO, 65211 USA.

4
Department of Electrical Engineering & Computer Science, College of Engineering,

University of Missouri, Columbia, MO, 65211 USA. 5Missouri University Center for

Research on Influenza Systems Biology (CRISB), University of Missouri, Columbia,

MO, 65211 USA. 6Bond Life Sciences Center, University of Missouri, Columbia, MO,

65211 USA. 7MU Informatics Institute, University of Missouri, Columbia, MO,

65211 USA. 8Guangdong Provincial Key Laboratory of Silviculture, Protection and

Utilization, Guangdong Academy of Forestry, Guangzhou, Guangdong Province

510520, China. 9Institute of Animal Health, Guangdong Academy of Agricultural

Sciences, Guangzhou, Guangdong Province 510640, China. 10Guangdong Provincial

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Wildlife Rescue Center, Guangzhou, Guangdong Province 510520 ,China.

*These authors contributed equally to this work.

†Corresponding author. Email: chenjp@giabr.gd.cn

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Abstract

The outbreak of 2019-nCoV pneumonia (COVID-19) in the city of Wuhan, China has

resulted in more than 70,000 laboratory confirmed cases, and recent studies showed

that 2019-nCoV (SARS-CoV-2) could be of bat origin but involve other potential

intermediate hosts. In this study, we assembled the genomes of coronaviruses

identified in sick pangolins. The molecular and phylogenetic analyses showed that

pangolin Coronaviruses (pangolin-CoV) are genetically related to both the

2019-nCoV and bat Coronaviruses but do not support the 2019-nCoV arose directly

from the pangolin-CoV. Our study also suggested that pangolin be natural host of

Betacoronavirus, with a potential to infect humans. Large surveillance of

coronaviruses in pangolins could improve our understanding of the spectrum of

coronaviruses in pangolins. Conservation of wildlife and limits of the exposures of

humans to wildlife will be important to minimize the spillover risks of coronaviruses

from wild animals to humans.

bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
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Introduction
In December 2019, there was an outbreak of pneumonia with an unknown cause

in Wuhan, Hubei province in China, with an epidemiological link to the Huanan

Seafood Wholesale Market, which is a live animal and seafood market. Clinical

presentations of this disease greatly resembled viral pneumonia. Through deep

sequencing on the lower respiratory tract samples of patients, a novel coronavirus

named the 2019 novel coronavirus (2019-nCoV) was identified [1]. Within less than 2

months, the viruses have spread to all provinces across China and 23 additional

countries. As of February 19, 2020, the epidemic has resulted in 72,532 laboratory

confirmed cases, 1,872 of which were fatal. With nearly three weeks of locking down

Wuhan (and followed by many other cities across China), the toll of new cases and

deaths are still rising.

To effectively control the diseases and prevent new spillovers, it is critical to

identify the animal origin of this newly emerging coronavirus. In this wet market of

Wuhan, high viral loads were reported in the environmental samples. However,

variety of animals, including some wildlife, were sold on this market, and the number

and species were very dynamics. It remains unclear which animal initiated the first

infections.

Coronaviruses cause respiratory and gastrointestinal tract infections and are

genetically classified into four major genera: Alphacoronavirus, Betacoronavirus,

Gammacoronavirus, and Deltacoronavirus. The former two genera primarily infect

mammals, whereas the latter two predominantly infect birds [2]. In addition to the

2019-nCoV, Betacoronavirus caused the 2003 SARS (severe acute respiratory

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syndrome) outbreaks and the 2012 MERS (Middle East respiratory syndrome)

outbreaks in humans [3, 4]. Both SARS-CoV and MERS-CoV are of bat origin, but

palm civets were shown to be an intermediate host for SARS-CoV [5] and dromedary

camels for MERS-CoV [6].

Approximate 30-thousand-base genome of coronavirus codes up to 11 proteins,

and the surface glycoprotein S protein binds to receptors on the host cell, initiating

virus infection. Different coronaviruses can use distinct host receptors due to

structural variations in the receptor binding domains of the virus S protein.

SARS-CoV uses angiotensin-converting enzyme 2 (ACE2) as one of the main

receptors [7] with CD209L as an alternative receptor [8], whereas MERS-CoV uses

dipeptidyl peptidase 4 (DPP4, also known as CD26) as the primary receptor.

Computational modeling analyses suggested that, similar to SARS-CoV, the

2019-nCoV uses ACE2 as the receptor [9].

Not soon after the release of the 2019-nCoV genome, a scientist released a full

genome of a coronavirus, Bat-CoV-RaTG13, from bat (Rhinolophus sinicus), which is

colonized in Yunan province, nearly 2,000 km away from Wuhan. Bat-CoV-RaTG13

was 96% identical at the whole genome level to the 2019-nCoV, suggesting the

2019-nCoV, could be of bat origin [10]. However, with rare direct contacts between

such bats and humans, similar to SARS-CoV and MERS-CoV, it seems to be more

likely that the spillover of 2019-nCoV to humans from another intermediate host

rather than directly from bats.

The goal of this study is to determine the genetic relationship between a

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coronavirus from two groups of sick pangolins and the 2019-nCoV and to assess

whether pangolins could be a potential intermediate host for the 2019-nCoV.

Results

In March of 2019, we detected Betacoronavirus in three animals from two sets of

smuggling Malayan pangolins (Manis javanica) (n=26) intercepts by Guangdong

customs [11]. All three animals suffered from serious respiratory diseases and failed

to be rescued by the Guangdong Wildlife Rescue Center [11] (Table S2). Through

metagenomic sequencing and de novo assembling, we recovered 38 contigs ranging

from 380 to 3,377 nucleotides, and the nucleotide sequence identities among the

contigs from these three samples were 99.54%. Thus, we pooled sequences from three

samples and assembled the draft genome of this pangolin origin coronavirus, so called

pangolin-CoV-2020 (Accession No.: GWHABKW00000000), which was

approximately 29,380 nucleotides, with approximately 84% coverage of the virus

genome (Figure 1a).

Strikingly, genomic analyses suggested the pangolin-CoV-2020 has a high

identity with both 2019-nCoV and Bat-CoV-RaTG13, the proposed origin of the

2019-nCoV [10] (Figure 1b; Figure 1c). The nucleotide sequence identity between

pangolin-CoV-2020 and 2019-nCoV was 90.23% whereas the protein sequence

identities for individual proteins can be up to 100% (Table S3; Table S4). The

nucleotide sequence between pangolin-CoV-2020 and Bat-CoV-RaTG13 was 90.15%

whereas that for the corresponding regions between 2019-nCoV and

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Bat-CoV-RaTG13 was 96.12% (Table 1).

The nucleotide sequence identities of the surface glycoprotein Spike (S) protein

genes between pangolin-CoV-2020 and 2019-nCoV was 82.21%, and the

Bat-CoV-RaTG13 and 2019-nCoV shared the highest sequence identity of 92.59%

(Table 1). There was a low similarity of 72.63% between the S genes of

pangolin-CoV-2020 and SARS-CoV. Nucleotide sequence analyses suggested the S

gene was relatively more genetic diverse in the S1 region than the S2 region (Figure

2a). Furthermore, the S proteins of pangolin-CoV-2020 and 2019-nCoV had a

sequence identity of 89.78% (Table 2), sharing a very conserved receptor binding

motif (RBM) (Figure S1), which is more conserved than in Bat-CoV-RaTG13. These

results support that pangolin-CoV-2020 and 2019-nCoV, and SARS-CoV could all

share the same receptor ACE2. The presence of highly identical RBMs in

pangolin-CoV-2020 and 2019-nCoV means that this motif was likely already present

in the virus before jumping to humans. However, it is interesting that both

pangolin-CoV-2020 and Bat-CoV-RaTG13 lack a S1/S2 cleavage site (~680-690 aa)

whereas 2019-nCoV possess (Figure S1).

Phylogenetic analyses suggested that the S genes of pangolin-CoV-2020,

2019-nCoV and three bat origin coronaviruses (Bat-CoV-RaTG13,

Bat-CoV-CVZXC21, and Bat-Cov-CVZC45) were genetically more similar to each

other than other viruses in the same family (Figure 2b). The S gene of

Bat-CoV-RaTG13 was genetically closer to each other than pangolin-CoV-2020,

Bat-CoV-CVZXC21, and Bat-Cov-CVZC45. Similar tree topologies were observed

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for the RdRp gene and other genes (Figure 3a-d; Figure S2a-h). At the whole genomic

level, the 2019-nCoV is also genetically closer to Bat-CoV-RaTG13 than

pangolin-CoV-2020 (Figure 1c).

Discussion

In this study, we assembled the genomes of coronaviruses identified in sick

pangolins and our results showed that a pangolin coronavirus (pangolin-CoV-2020) is

genetically associated with both 2019-nCoV and a group of bat coronaviruses. There

is a high sequence similarity between pangolin-CoV-2020 and 2019-nCoV. However,

phylogenetic analyses did not support the 2019-nCoV arose directly from the

pangolin-CoV-2020.

It is of interest that the genomic sequences for coronaviruses detected from two

batches of pangolins intercepted by two different customs at different dates were all

be associated with bat coronaviruses. The reads from the third pangolin acquired in

July of 2019 were relatively less abundant than the two from the first two pangolin

samples acquired in March of 2019. Although we are unclear whether these two

batches of smuggling and exotic pangolins were from the same origin, our results

indicated that pangolin be a natural host for Betacoronaviruses, which could be

enzootic in pangolins. All three exotic pangolins detected with Betacoronaviruses in

this study were very sick with serious respiratory diseases and failed to be rescued.

However, these pangolins were very stressful in the transportation freight when being

intercepted by the customs. It is unclear whether this coronavirusis a common virus

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flora in the respiratory tracts of pangolins. Nevertheless, the pathogenesis of this

coronavirus to pangolin remains to be studied.

Compared to the genomic sequence of pangolin-CoV-2020 we assembled in this

study, phylogenetic trees suggested that a bat origin coronavirus (i.e.,

Bat-CoV-RaTG13) was more genetically close to the 2019-nCoV at both individual

gene and genomic sequence level. Interestingly, the cleavage site between S1 and S2

at the 2019-nCoV had multiple insertions (i.e. PRRA), compared to that of

Bat-CoV-RaTG13 and pangolin-CoV-2020, which were similar. Thus, although it is

clear that 2019-nCoV is of bat origin, it is likely another intermediate host could be

involved in emergence of the 2019-nCoV.

The S protein of coronaviruses bind to host receptors via receptor-binding

domains (RBDs), and plays an essential role in initiating virus infection and

determines host tropism [2]. A prior study suggested that the 2019-nCoV, SARS-CoV,

and Bat-CoV-RaTG13 had similar RBDs, suggested all of them use the same receptor

ACE2 [9]. Our analyses showed that pangolin-CoV-2020 had a very conserved RBD

to these three viruses rather than MERS-CoV, suggesting that pangolin-CoV is very

likely to use ACE2 as its receptor. On the other hand, ACE2 receptor is present in

pangolins with a high sequence conservation with those in the gene homolog in

humans. However, the zoonosis of this pangolin-CoV-2020 remains unclear.

The host range of animal origin coronaviruses was promiscuous [12]. It is critical

to determine the natural reservoir and the host range of coronaviruses, especially their

potential of causing zoonosis. In the last two decades, besides the 2019-nCoV, SARS
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and MERS caused serious outbreaks in humans, lead to thousands of deaths [3, 4, 13,

14]. Although all of three zoonotic coronaviruses were shown to be of bat origin, they

seemed to use different intermediate hosts. For example, farmed palm civets were

suggested to be an intermediate host for SARS to be spilled over to humans although

the details on how to link bat and farmed palm civets are unclear [15, 16, 17]. Most

recently, dromedary camels in Saudi Arabia were shown to harbor three different

coronavirus species, including a dominant MERS-CoV lineage that was responsible

for the outbreaks in the Middle East and South Korea during 2015 [18]. Although this

present study does not support pangolins would be an intermediate host for the

emergence of the 2019-nCoV, our results do not prevent the possibility that other

CoVs could be circulating in pangolins. Thus, large surveillance of coronaviruses in

the pangolins could improve our understanding the spectrum of coronaviruses in the

pangolins. Conservation of wildlife and limits of the exposures of humans to wildlife

will be important to minimize the spillover risks coronaviruses from wild animals to

humans.

In summary, this study suggested pangolins be a natural host of Betacoronavirus,

with an unknown potential to infect humans. However, our data do not support the

2019-nCoV evolved directly from the pangolin-CoV.

Materials and Methods

Data selection. During our routine wildlife rescue efforts, one of the goals was to
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identify pathogens causing wildlife diseases. In 2019, we were involved in two events

of pangolin rescues, one involved with 21 smuggling pangolins in March and the

second with 6 smuggling pangolins in July. From those pangolins failed to be rescued,

we collected samples from different tissues and subjected for metagenomic analyses.

Through viral metagenomics analyses of lower respiratory tract samples from these

pangolins, we detected coronavirus in three individual animals [11]. Two of these

animals were from the first batch of Malayan pangolins intercepted by Meizhou,

Yangjiang, and Jiangmen customs, and the third one was from the second batch in a

freight being transported from Qingyuan to Heyuan. The RNA samples from these

three individuals were subjected to deep sequencing. To determine the read abundance

of coronaviruses in each sample, we mapped clean reads without ribosomes and host

sequences to an in-house virus reference data separated from the GenBank

non-redundant nucleotide database.

Genomic assembly and sequence analyses. After examining the high similarity

among the samples from three animals, to maximize the coverage of the virus genome,

clean reads from three animals were pooled together and de novo assembled using

MEGAHIT v1.2.9 [19]. The assembled contigs were used as references for mapping

those the rest unmapped reads using Salmon v0.14.1 [20], and multiple rounds were

implemented to maximize the mapping (Table S2).

A total of 38 contigs were identified to be highly similar to the 2019-nCoV

genome (accession MN908947.3) using BLASTn and tBLASTx. GapFiller v1.10 and
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SSPACE v3.0 were used to fill gaps and draft pangolin-CoV-2020 genome was

constructed with ABACAS v1.3.1 (http://abacas.sourceforge.net/) [21, 22, 23].

Multiple sequence alignments were conducted using CLUSTAL Ov1.2.4 [24].

Simplot analyses were conducted with SimPlot v3.5.1 to determine the sequence

similarity among 2019-nCoV (MN908947.3), pangolin-CoV-2020, Bat-CoV-RaTG13

(MN996532.1), and SARS-CoV (AY395003.1) at both the genomic sequence level

and at individual gene level [25]. Sequence identity was calculated utilizing

p-diatance in MEGA v10.1.7 [26].

Phylogenetic analyses. We downloaded 44 full-length genome sequences of

coronaviruses isolated from different hosts from the public database (Table S1).

Phylogenetic analyses were performed based on their whole genome sequences,

encoding ORFs of RNA-dependent RNA polymerase (RdRp gene), the receptor

binding protein spike protein (S gene), small envelope protein (E gene), as well as all

other gene sequences were conducted utilizing Mrbayes [27] with 50,000,000

generations and the 25% of the generations as burnin. Best models were determined

by jModeltest v2.1.7 [28]. Then, all the trees were visualized and exported as vector

diagrams with FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/).

Acknowledgements: We thank the De-Chun Lin and Tao Jin from Magigene Biotech.

and Hanghui Kong from South China Botanical Garden support for bioinformatics

analysis. This project was supported by wildlife disease monitoring and early warning
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system maintenance project from National Forestry and Grassland Administration

(2019072), GDAS Special Project of Science and Technology Development (grant

number 2020GDASYL-20200103090, 2018GDASCX-0107),Guangzhou Science

Technology and Innovation Commission (grant number 201804020080), Natural

Science Foundation of China (grant number 31972847), Guangzhou science and

technology project (grant number 2019001), and 2019-nCoV wildlife origin project

from Guangdong department of science and technology.

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Tables
Table 1. Nucleotide sequence identities among the genes of pangolin-CoV-2020 and other representative coronavirus against 2019 nCoV.

Genes (%)
S E M N ORF1a ORF1b RDRP ORF3a ORF6 ORF7a ORF7b ORF10
Pangolin-CoV-2020 83.05 99.11 93.38 95.58 89.33 89.66 91.28 92.36 95.53 93.39 91.47 99.15
Bat-CoV-RaTG13 93.11 99.55 95.93 96.90 96.04 97.31 97.80 96.24 98.36 95.59 99.22 99.15
Bat-CoV-CVZXC21 76.79 98.67 93.39 91.17 90.93 86.17 86.99 88.85 95.08 89.62 95.35 100.00
Bat-Cov-CVZC45 77.19 98.67 93.39 91.09 91.03 86.07 86.70 87.76 95.08 89.31 94.57 99.15
SARS 74.54 94.44 85.37 88.78 76.08 86.26 88.65 75.55 76.50 84.11 86.18 93.16

Table 2. Protein sequence identities among the genes of pangolin-CoV-2020 and other representative coronavirus against 2019 nCoV.

Amino acid (%)

S E M N ORF1a ORF1b RDRP ORF3a ORF6 ORF7a ORF7b ORF10
Pangolin-CoV-2020 89.78 100.00 98.63 97.06 95.84 99.20 99.34 97.03 96.49 97.49 95.24 97.30
Bat-CoV-RaTG13 97.69 100.00 99.55 99.04 98.07 99.37 99.57 97.79 100.00 97.49 97.65 97.30
Bat-CoV-CVZXC21 82.08 100.00 98.64 94.10 95.72 95.51 95.69 91.66 93.22 90.09 92.77 100.00
Bat-Cov-CVZC45 82.66 100.00 98.64 94.10 95.74 95.81 96.03 90.47 93.22 89.04 92.77 97.30
SARS 78.30 95.74 90.02 90.76 80.90 95.63 96.48 96.80 62.68 88.11 84.18 82.31
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
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Figure legends

Figure 1. Genomic comparison of pangolin-CoV-2020, 2019-nCoV, and other

coronaviruses. a) genomic alignment of pangolin-CoV-2020 and 2019-nCoV, white

indicates missing sequence; b) Similarity plot based on the full-length genome

sequence of 2019-nCoV. Full-length genome sequences of Bat-CoV-RaTg13,

Bat-CoV-SL-CoVZXC21, SARS, and pangolin-CoV-2020 draft genome were used as

subject sequences; c) Phylogenetic tree based on nucleotide sequences of complete

genomes of coronaviruses.

Figure 2. Genetic analyses of the spike surface glycoprotein of

pangolin-CoV-2020, 2019-nCoV, and other coronaviruses. a) similarity plot based

on the spike surface glycoprotein amino acid and nucleotide sequence of 2019-nCoV.

Bat-CoV-RaTg13, and pangolin-CoV-2020 were used as subject sequences; b)

phylogenetic tree of S genes.

Figure 3. Phylogenetic analyses of a) small envelope gene, b) RNA-dependent

RNA polymerase (RdRp) gene, c) matrix protein, and d) nucleocapsid protein

sequences of coronaviruses from different hosts.

bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission.

Supplementary Information

Supplementary Tables

Table S1. Accession numbers and strain IDs of coronaviruses strains isolated from

different hosts.

Table S2. Number of sequencing reads assigned to different viruses in each pangolin

sample. We only focus on Coronaviruses in this study.

Table S3. The blast results for the assembled nucleotide contigs of

pangolin-CoV-2020 and 2019-nCoV.

Table S4. The blast results for the translated proteins from assembled nucleotide

contigs of pangolin-CoV-2020 and 2019-nCoV.

bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission.

Supplementary Figures

Figure S1. Amino acid sequence alignment of the spike surface glycoprotein of the

Pangolin-CoV-2020 with 2019-nCoV and Bat-CoV-RaTG13.

Figure S2. Phylogenetic analyses of a) ORF1a, b) ORF1b, c) ORF3a, d) ORF6, e)

ORF7a, f) ORF7b, g) ORF8, and h) ORF10 gene sequences of coronaviruses

from different hosts.

Figure 1a
2019-nCoV

Pangolin-CoV-2020
Figure 1b 7a 7b

ORF1a ORF1b S 3a N

E M6 8
1.0
Percentage nucleotide identity

0.9

0.8

0.7

0.6

0.5

0.4
0 5000 10000 15000 20000 25000 30000

Bat-CoV-RaTG13 Pangolin-CoV-2020 Bat-CoV-SL-CoVZXC21 SARS

 Figure 1c AY394996.1_SARS_ZS_B
100

AY395003.1_SARS_ZS_C
96 AY278489.2_SARS_GD01
100
97 AY390556.1_SARS_GZ02
100
AY394981.1_SARS_HGZ8L1_A
AY686864.1_SARS_B039
100
100
AY572035.1_SARS_civet010

KY417150.1_Bat_CoV_Rs4874
100
100
KT444582.1_Bat_CoV_WIV16

KC881006.1_Bat_CoV_Rs3367
100
100
KF367457.1_Bat_CoV_WIV1
100
KY417151.1_Bat_CoV_Rs7327
100
100 MK211376.1_Bat_CoV_YN2018B
KJ473816.1_Bat_CoV_YN2013

100 KY417143.1_Bat_CoV_Rs4081
100
MK211378.1_Bat_CoV_YN2018D
100
KY417142.1_Bat_CoV_As6526
100
MK211377.1_Bat_CoV_YN2018C
100
MK211375.1_Bat_CoV_YN2018A
100 DQ071615.1_Bat_CoV_Rp3
100
KJ473815.1_Bat_CoV_GX2013
100
KP886808.1_Bat_CoV_YNLF_31C
KU973692.1_Bat_CoV_F46
100
100
100 JX993988.1_Bat_CoV_Yunnan2011
KF569996.1_Bat_CoV_LYRa11
MK211374.1_Bat_CoV_SC2018
100
KJ473814.1_Bat_CoV_HuB2013
100
DQ412043.1_Bat_CoV_Rm1
100
83 DQ648857.1_Bat_CoV_BtCoV_279_2005
JX993987.1_Bat_CoV_Rp_Shaanxi2011
100
KJ473811.1_Bat_CoV_JL2012
100
100 DQ412042.1_Bat_CoV_Rf1
100
DQ648856.1_Bat_CoV_BtCoV_273_2005
100
KJ473812.1_Bat_CoV_HeB2013
100
KJ473813.1_Bat_CoV_SX2013

KF294457.1_Bat_CoV_Longquan_140
100 100
GQ153544.1_Bat_CoV_HKU3_9
100
DQ022305.2_Bat_CoV_HKU3_1
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission. 100
DQ084200.1_Bat_CoV_HKU3_3

100 MN996532.1_Bat_CoV_RaTG13
100 MN908947.3_2019_nCoV
100 Pangolin-CoV-2020

100 MG772933.1_Bat_CoV_CVZC45
MG772934.1_Bat_CoV_CVZXC21
KY352407.1_Bat_CoV_BtKY72

0.2
 Figure 2a

100%
Nucleotide Identity

80%

60%

40%

20%
0 500 1000 1500 2000 2500 3000 3500
SP TM

NTD RBD RBM FP HR1 HR2

CP
Amino acid Identity

100%
90%
80%
70%
60%
0 200 400 600 800 1000 1200
Bat-CoV_RaTG13 Pan-CoV
 KU973692.1_Bat_CoV_F46
100
Figure 2b
KJ473811.1_Bat_CoV_JL2012
100
KJ473812.1_Bat_CoV_HeB2013
100
KJ473813.1_Bat_CoV_SX2013
96
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
100
author/funder. All rights reserved. DQ412042.1_Bat_CoV_Rf1
No reuse allowed without permission.
100
DQ648856.1_Bat_CoV_BtCoV_273_2005
100
KP886808.1_Bat_CoV_YNLF_31C

JX993988.1_Bat_CoV_Yunnan2011

KJ473815.1_Bat_CoV_GX2013

100 KF294457.1_Bat_CoV_Longquan_140

100 100 DQ022305.2_Bat_CoV_HKU3-1

99
DQ084200.1_Bat_CoV_HKU3-3
100
81
GQ153544.1_Bat_CoV_HKU3-9

DQ412043.1_Bat_CoV_Rm1
100
DQ648857.1_Bat_CoV_BtCoV_279_2005
100
100
DQ071615.1_Bat_CoV_Rp3

100 KY417143.1_Bat_CoV_Rs4081
100
MK211378.1_Bat_CoV_YN2018D
100
MK211375.1_Bat_CoV_YN2018A

100
KY417142.1_Bat_CoV_As6526
100
MK211377.1_Bat_CoV_YN2018C

94
MK211374.1_Bat_CoV_SC2018

100
KJ473814.1_Bat_CoV_HuB2013
100
JX993987.1_Bat_CoV_Rp_Shaanxi2011

MG772933.1_Bat_CoV_CVZC45
100
MG772934.1_Bat_CoV_CVZXC21
100
100 Panolin-CoV-2020

100
MN908947.2_2019_nCoV
100
MN996532.1_Bat_CoV_RaTG13

KF569996.1_Bat_CoV_LYRa11

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100
KY417151.1_Bat_CoV_Rs7327
100 100
KC881006.1_Bat_CoV_Rs3367
98
KF367457.1_Bat_CoV_WIV1

100
KY417150.1_Bat_CoV_Rs4874
100
KT444582.1_Bat_CoV_WIV16

100 AY278489.2_SARS_GD01
80
AY390556.1_SARS_GZ02
100
AY686864.1_SARS_B039
100
AY572035.1_SARS_civet010

KJ473816.1_Bat_CoV_YN2013

0.08
 DQ648856.1_Bat_CoV_BtCoV_273_2005
89
Figure 3a DQ412042.1_Bat_CoV_Rf1
100
KJ473812.1_Bat_CoV_HeB2013
87
KJ473813.1_Bat_CoV_SX2013

KJ473811.1_Bat_CoV_JL2012
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission.
MK211375.1_Bat_CoV_YN2018A

KJ473816.1_Bat_CoV_YN2013

DQ071615.1_Bat_CoV_Rp3

KF569996.1_Bat_oV_LYRa11

GQ153544.1_Bat_CoV_HKU3_9

DQ022305.2_Bat_CoV_HKU3_1

DQ084200.1_Bat_CoV_HKU3_3

KF294457.1_Bat_CoV_Longquan_140

DQ648857.1_Bat_CoV_BtCoV_279_2005
98
DQ412043.1_Bat_CoV_Rm1

JX993987.1_Bat_CoV_Rp_Shaanxi2011

50 KJ473814.1_Bat_CoV_HuB2013

KJ473815.1_Bat_CoV_GX2013
77
KU973692.1_Bat_CoV_F46

JX993988.1_Bat_CoV_Yunnan2011

MK211374.1_Bat_CoV_SC2018

AY394981.1_SARS_HGZ8L1_A

AY572035.1_SARS_civet010

KP886808.1_Bat_CoV_YNLF_31C

AY686864.1_SARS_B039

51 KY417142.1_Bat_CoV_As6526

MK211378.1_Bat_CoV_YN2018D
85
MK211376.1_Bat_CoV_YN2018B

AY394996.1_SARS_ZS_B

AY278489.2_SARS_GD01

AY395003.1_SARS_ZS_C
94
KY417143.1_Bat_CoV_Rs4081

MK211377.1_Bat_CoV_YN2018C

AY390556.1_SARS_GZ02

KY417151.1_Bat_CoV_Rs7327

KC881006.1_Bat_CoV_Rs3367
100
KF367457.1_Bat_CoV_WIV1

KT444582.1_Bat_CoV_WIV16

KY417150.1_Bat_CoV_Rs4874

MG772934.1_Bat_CoV_CVZXC21
93
MG772933.1_Bat_CoV_CVZC45
100
Pangolin-CoV-2020

MN996532.1_Bat_CoV_RaTG13

MN908947.3_2019_nCoV

KY352407.1_Bat_CoV_BtKY72

0.008
 MK211374.1_Bat_CoV_SC2018
Figure 3b
KU973692.1_Bat_CoV_F46
77
KP886808.1_Bat_CoV_YNLF_31C

97
AY572035.1_SARS_civet010
100
AY686864.1_SARS_B039
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628 . The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission.
82 AY278489.2_SARS_GD01

94 AY395003.1_SARS_ZS_C

AY394996.1_SARS_ZS_B

100 AY390556.1_SARS_GZ02

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KC881006.1_Bat_CoV_Rs3367
100
KF367457.1_Bat_CoV_WIV1
59

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100
KY417150.1_Bat_CoV_Rs4874
100
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72 MK211377.1_Bat_CoV_YN2018C

MK211378.1_Bat-CoVYN_2018D
99
64
KJ473816.1_Bat_CoV_YN2013

100 KY417151.1_Bat_CoV_Rs7327

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100
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100
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94 KF569996.1_Bat_CoV_LYRa11

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100
MN908947.3_2019_nCoV
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100
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MG772933.1_Bat_CoV_CVZC45

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100
DQ648857.1_Bat_CoV_BtCoV_279_2005
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DQ648856.1_Bat-CoVBtCoV_273_2005
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100
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KJ473813.1_Bat_CoV_SX2013

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 KC881006.1_Bat_CoV_Rs3367
Figure 3c
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KT444582.1_Bat_CoV_WIV16
99
KY417150.1_Bat_CoV_Rs4874
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission.
MK211376.1_Bat_CoV_YN2018B
99
MK211378.1_Bat_CoV_YN2018D

MK211375.1_Bat_CoV_YN2018A

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97
96
KJ473811.1_Bat_CoV_JL2012

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100
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97
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MK211377.1_Bat_CoV_YN2018C

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100
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100
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57
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100
MG772933.1_Bat_CoV_CVZC45
99

66 Pangolin-CoV-2020

MN996532.1_Bat_CoV_RaTG13
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MN908947.3_2019_nCoV

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 MK211374.1_Bat_CoV_SC2018

Figure 3d MK211375.1_Bat_CoV_YN2018A

KJ473815.1_Bat_CoV_GX2013

DQ071615.1_Bat_CoV_Rp3

KF569996.1_Bat_CoV_LYRa11
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.18.954628. The copyright holder for this preprint (which was not peer-reviewed) is the
author/funder. All rights reserved. No reuse allowed without permission. 76
KU973692.1_Bat_CoV_F46

MK211376.1_Bat_CoV_YN2018B
100
MK211378.1_Bat_CoV_YN2018D

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100
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KY417150.1_Bat_CoV_Rs4874

KJ473816.1_Bat_CoV_YN2013

KJ473814.1_Bat_CoV_HuB2013
93
DQ412043.1_Bat_CoV_Rm1
100
91 DQ648857.1_Bat_CoV_BtCoV_279_2005

JX993987.1_Bat_CoV_Rp_Shaanxi2011

GQ153544.1_Bat_CoV_HKU3_9
100
DQ084200.1_Bat_CoV_HKU3_3
100
99
100 DQ022305.2_Bat_CoV_HKU3_1

KF294457.1_Bat_CoV_Longquan_140

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KJ473813.1_Bat_CoV_SX2013
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KJ473812.1_Bat_CoV_HeB2013
80
DQ648856.1_Bat_CoV_BtCoV_273_2005
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MG772934.1_Bat_CoV_CVZXC21
100
Pangolin-CoV-2020
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MN908947.3_2019_nCoV
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MN96532.1_Bat_CoV_RaTG13

KY352407.1_Bat_CoV_BtKY72

0.04