Single-Cell Transcriptional Atlas of the Chinese Horseshoe Bat

Home , BSCL2, HSH2D, Yinpterochiroptera

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1 Single-cell transcriptional atlas of the Chinese horseshoe bat

2 (Rhinolophus sinicus) provides insight into the cellular

3 mechanisms which enable bats to be viral reservoirs

5 Lili Ren,1,2,# Chao Wu,1,2,# Li Guo,1,2,# Jiacheng Yao,3,# Conghui Wang,1 Yan Xiao,1,2

6 Angela Oliveira Pisco,4 Zhiqiang Wu,2,5 Xiaobo Lei,1 Yiwei Liu,1 Leisheng Shi,6 Lianlian

7 Han,1 Hu Zhang,1 Xia Xiao,1 Jingchuan Zhong,1 Hongping Wu,3 Mingkun Li,6,7 Stephen

8 R. Quake,4,8 Yanyi Huang,9,10, * Jianbin Wang,3,11,12, * and Jianwei Wang,1,2,*

10 1 NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux

11 Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences &

12 Peking Union Medical College, Beijing 100730, China

13 2 Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical

14 Sciences and Peking Union Medical College, Beijing, 100730, China

15 3 School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua

16 University, Beijing 100084, China

17 4 Chan Zuckerberg Biohub, San Francisco, CA 94158, USA

18 5 NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology,

19 Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730,

20 China

21 6 Beijing Institute of Genomics, Chinese Academy of Sciences, and China National

22 Center for Bioinformation, Beijing, 100101, China

1 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

23 7 Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences,

24 Kunming, 650223, China

25 8 Departments of Bioengineering and Applied Physics, Stanford University, Stanford, CA

26 94305, USA

27 9 Biomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation

28 Center for Genomics (ICG), College of Chemistry, and Peking-Tsinghua Center for Life

29 Sciences, Peking University, Beijing 100871, China

30 10 Institute for Cell Analysis, Shenzhen Bay Laboratory, Guangdong 518132, China

31 11 Beijing Advanced Innovation Center for Structural Biology (ICSB), Tsinghua

32 University, Beijing 100084, China

33 12 Chinese Institute for Brain Research (CIBR), Beijing 102206, China

34 # These authors contributed equally.

35 *Correspondence: [email protected] (Jianwei W.),

36 [email protected] (Jianbin W.), [email protected] (Y.H.)

2 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

39 Abstract

40 Bats are a major “viral reservoir” in nature and there is a great interest in not only the

41 cell biology of their innate and adaptive immune systems, but also in the expression

42 patterns of receptors used for cellular entry by viruses with potential cross-species

43 transmission. To address this and other questions, we created a single-cell transcriptomic

44 atlas of the Chinese horseshoe bat (Rhinolophus sinicus) which comprises 82,924 cells

45 from 19 organs and tissues. This atlas provides a molecular characterization of numerous

46 cell types from a variety of anatomical sites, and we used it to identify clusters of

47 transcription features that define cell types across all of the surveyed organs. Analysis of

48 viral entry receptor genes for known zoonotic viruses showed cell distribution patterns

49 similar to that of humans, with higher expression levels in bat intestine epithelial cells. In

50 terms of the immune system, CD8+ T cells are in high proportion with tissue-resident

51 memory T cells, and long-lived effector memory nature killer (NK) T-like cells (KLRG1,

52 GZMA and ITGA4 genes) are broadly distributed across the organs. Isolated lung primary

53 bat pulmonary fibroblast (BPF) cells were used to evaluate innate immunity, and they

54 showed a weak response to interferon β and tumor necrosis factor-α compared to their

55 human counterparts, consistent with our transcriptional analysis. This compendium of

56 transcriptome data provides a molecular foundation for understanding the cell identities,

57 functions and cellular receptor characteristics for viral reservoirs and zoonotic

58 transmission.

60 Key words: bat, single-cell sequencing, immunity, receptor, zoonotic

3 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

62 Introduction

63 Bats function as natural viral reservoirs and are distributed globally; they are unique

64 as flying mammals. They have high diversity with more than 1,300 bat species having

65 been identified [http://www.batcon.org]1,2. Bats carry some of the deadliest viruses for

66 humans, including lyssaviruses, Ebola (EBOV) and Marburg (MARV) filoviruses, severe

67 acute respiratory syndrome coronaviruses (SARS-CoV)-like viruses (SL-CoVs), Middle

68 East respiratory syndrome (MERS-CoV)-like viruses (ML-CoVs), Hendra (HeV) and

69 Nipah (NiV) henipaviruses3,4. SARS-CoV-2, which emerged in December 2019 and

70 caused a global pandemic, is also considered as originating in bats5,6.

71 Bats have evolved over eons to sustain infection from pathogens without

72 succumbing to overt disease, which indicates a uniquely powerful immune system7.

73 According to the comparative genome and transcriptome studies, in vitro bat cell culture,

74 and experimental infection assays, the diverse bat species may have evolved different

75 mechanisms to balance between enhanced immune function which clears viral infections

76 and tolerance on limiting immunopathology1,8. However, knowledge of bat immunology

77 is still poorly understood as current studies used mainly Pteropus alecto, Myotis davidii,

78 and Rousettus aegyptiacus species, but obtained conflicting findings on the function of

79 bat immune systems9,10. The natural killer (NK) cells and type I interferons (IFNs)

80 signaling pathways are of great interest. It has been reported a few NK cell receptor genes,

81 killer cell lectin-like receptor genes (KLRD and KLRC), exist in the Pteropus alecto

82 transcriptome and Rousettus aegyptiacus genome11. However, the majority of known

83 canonical NK cell receptor genes are absent in currently known bat genomes10,12.

84 As they have a long life span and continued natural selection, the bat has also been

85 considered as an excellent model to study human cellular evolution features compared to

86 other lab animals1. Characterizing the extent to which bat cellular biological functions

87 mirrors those of humans will enable scientists to understand the characteristics of the

88 immune system and mechanisms of the zoonotic virus spreading. The exploration of the

89 organs in single cell level in human, model mouse has provided insights into cellular

90 diversity and revealed new cell types related to physiological function13-15 .

91 In this study we report the molecular composition of 89 cell types from the Chinese

92 horseshoe bat (Rhinolophus sinicus), belonging to suborder of Yinpterochiroptera, a

93 natural reservoir of SL-CoVs. The compendium comprises single-cell transcriptomic data

94 from cells of 19 organs, including adipose tissues (brown and white), bladder, bone

95 marrow, brain, heart, intestine, kidney, liver, lung, muscle, pancreas, wing membrane,

96 spleen, testis, thymus, tongue, trachea and whole blood.

98 Results

99 Transcriptomic characteristics

100 To ensure accuracy of the single cell sequencing (sc-seq), 12 of the 19 obtained

101 organs were firstly analyzed by using bulk sequencing (bulk-seq), including adipose

102 tissues (brown and white), brain, heart, intestine, kidney, liver, lung, muscle, spleen,

103 tongue, and trachea (Fig. 1a). As the interaction of the virus with its cellular receptor is a

104 key step in its pathogenesis16, we first compared the transcriptomic patterns of viral

105 receptor genes in different mammals: bat, human and mouse. We analyzed 6 out of 28

106 known human viral receptor genes as representatives (Fig. 1b), in which five are known

107 bat zoonotic virus receptors: angiotensin convert enzyme 2 (ACE2) (receptor of

108 SARS-CoV, SARS-CoV-2 and human coronavirus (HCoV) NL63), dipeptidyl peptidase 4

109 (DPP4), (receptor of MERS-CoV), aminopeptidase N (ANPEP) (receptor of

110 HCoV-229E)17, Ephrin-B2 (EFNB2) (receptor of HeV and NiV), NPC intracellular

111 cholesterol transporter 1 (NPC1) (receptor of EBOV and MARV), coxsackievirus and

112 adenovirus receptor [CXADR, the human and bat adenovirus (Adv) shared receptor]18.

113 Transmembrane serine protease 2 (TMPRSS2), a protease essential for SARS-CoV and

114 SARS-CoV-2 entry was also analyzed (Fig. 1b). The data show that TMPRSS2, DPP4

115 and ANPEP express at high levels in the lung, intestine and kidney in bat, human and

116 mouse. Although ACE2 is also highly expressed in the intestine and kidney of all three

117 species, for lung it expresses highly in only mouse but not in human or bat (Fig. 1b, 1c).

118 Both the ACE2 and TMPRSS2 genes highly express in bat tongue, while only ACE2

119 highly expresses in mouse tongue and only TMPRSS2 in human tongue. In the heart,

120 brain, spleen, wing (skin), muscle and adipose tissues, only ACE2 shows highly

121 expressed in two of the species, but TMPRSS2 shows low expression levels. The neural

122 cell adhesion molecule 1 (NCAM1) gene, Rabies virus (RABV) receptor, is found mainly

123 expressed in the brain of all three species, as well as in the human heart, spleen and

124 muscle. The EFNB2 and NPC1 are distributed in most of the organs in bat, human and

125 mouse with similar expression level. Such distribution characteristics may be related to

126 the multiple organs involved infections of HeV, NiV and EBOV19,20. Of the other 20 viral

127 receptor genes, we notice that most of the genes express in a similar patterns between bat

128 and human, except the low-density lipoprotein receptor (LDLR) gene, the receptor gene

129 of human rhinovirus, which showes a low expression level in bat intestine and lung

130 compared to that of human (Extended Data Fig. 1a). Therefore, at the level of bulk

131 transcriptomic analysis, it is clear that the ability of bats to avoid overt disease from these

132 viruses is not due to species specific expression of entry receptors in particular tissues.

133 Construction of single-cell atlas of bat

134 For sc-seq, nearly all tissues were obtained from both bats, with the exception of the

135 intestine and white adipose tissue (Fig. 1a). Overall, 82,924 cells were retained after

136 quality control. The median number of unique molecular identifiers (UMIs) per cell is

137 3,081 (Extended Data Fig. 1b). The organs were analyzed independently and cells were

138 clustered according to the highly variable genes between cells by principal component

139 analysis (PCA) and nearest-neighbour graph. A total of the 182 clusters were defined

140 from the 19 organs (Extended Data Fig. 1c, Supplementary Table 1). The cell types in

141 each cluster were annotated using known genes with differential expression between

142 clusters. Significant differential transcriptional genes were observed across cell types,

143 which encompass the gene module repertoire of the bat (Fig. 1d, 1e, Extended Data Fig.

144 1c). To ensure the accuracy of the single-cell (sc)-RNA seq data for cell typing, we

145 further analyzed these differential transcriptional genes and found the similar expression

146 pattern in corresponding organs in the bulk-seq data (Extended Data Fig. 1d). We

147 constructed a bat cell atlas (http://bat.big.ac.cn/) for data accessing, enabling the

148 searching of interested genes and browsing of single-cell data for all the organs.

149 To define whether there are varying gene transcription levels in different species at

150 the single cell level, we explored differential gene expression by using the data from the

151 bat lung and compared to that of human and mouse. In the bat lung, total 19 distinct

152 clusters were classified, including 4 epithelial cells [alveolar epithelial type 1 (AT1) cell,

153 alveolar epithelial type 2 (AT2) cell, ciliated cell, and mesothelial cell)], 3 endothelial

154 cells (capillary type 1 cell, capillary type 2 cell, and lymphatic cell), 3 mesenchymal cells

155 (adventitial fibroblast, alveolar fibroblast, and myofibroblast), 9 immune cell types

156 (alveolar macrophage, interstitial macrophage, classical monocyte, non-classical

157 monocyte, B cell, T cell, natural killer T cell, neutrophil and ALOX5AP+ macrophage )

158 and one untyped cell cluster, which shows no specific expressed gene compared to other

159 clusters (Fig. 2a, Extended Data Fig. 2 a-c). The differential genes expressed in epithelial

160 cells, endothelial cells, mesenchymal and immune cells of lung across the species were

161 then analyzed (Fig. 2b, Supplementary Table 2). In all the cell types, DAZAP221, related

162 to the regulation of innate immunity and SUMO222，redundantly prevent host interferon

163 response, were expressed at a higher level in bat compared to that of mouse. The genes

164 related to cell proliferation (MED28, TEMD3) 23,24, cell cycle (GATAD1) 25, regulation of

165 apoptosis and cell death (ITM2C) 26, host defense and inflammatory response (CTSL)

166 27expressed in higher levels in bat epithelial cells, endothelial cells and mesenchymal

167 cells, while the TAPBP28, associated with antigen presentation, and ARHGD1A29, the

168 regulator of Rho activity expressed higher in bat immune cells.

169 When compared to that of human, higher expression of several genes across the bat

170 cell types were observed, including PSMA6, related to the inflammatory response30;

171 GABARAP, a mediator of autophagy and apoptosis31; CDO1, the tumor suppressor genes

172 32; and RNASE433 , a member of RNase family associated with host defense-related

173 activities, assumed to interact with pathogen-derived nucleic acid and facilitate their

174 presentation to innate immune receptors within the cell as immunomodulatory proteins.

175 Notably, the gene expressed ribonuclease kappa (RNASEK)34, recently identified as a

176 host dispensable factor for the uptake of acid-dependent viruses, was highly expressed in

177 bat lung cells (Fig. 2b and Supplementary Table 2). In bat lung epithelial cells, the gene

178 encoded Heme oxygenase-1 (HMOX1), were observed at a higher level; this gene has

179 been recognized as having anti-inflammatory properties and anti-viral activity35,36. In the

180 bat monocytes, macrophages and mast cells, ITGA4 and IRF9 were expressed more

181 highly compared to that of human. This well-characterized bat altas can gain an insight

182 into cellular heterogeneity at the single cell resolution.

183 For viruses with respiratory and enteric tropism, we analyzed the viral receptor gene

184 expression level across the cells (Fig. 2c, Extended Data Fig. 2d-g, Extended Data Fig. 3).

185 This analysis shows that the respiratory virus receptor genes, ACE2, DPP4, ANPEP and

186 CXADR are expressed at a high level in enterocytes, cell cycle-associated cells,

187 enteroendocrine cells in the intestine, proximal straight tubule epithelial cells, and

188 collecting duct epithelial cell (principal cells) in the kidney, and also in AT1, ciliated cells

189 and mesothelial cells in the lung (Fig. 2c). NCAM1 transcripts are mainly in

190 oligodendrocyte precursor cells, oligodendrocytes, and astrocytes in the brain. EFNB2 is

191 mainly expressed in endothelial cells in the spleen, heart, and intestine, which is

192 consistent with the NiV and HeV secondary replication sites, and corresponds to their

193 important role in virus dissemination19. In addition, EFNB2 is also expressed in intestine

194 epithelial cells, but at a relatively low level, where NiV antigen have been identified in

195 fatal human cases19. The expression of NPC1 is broadly distributed in epithelial cells,

196 endothelial cells, and mesenchymal cells.

197 The distribution patterns and expression levels of these receptor genes were then

198 analyzed in human and mouse. We focused on the receptor genes (ACE2, DPP4, and

199 ANPEP) of known zoonotic respiratory viruses, shared receptor of human and bat

200 (CXADR) and TMPRSS2 in the cell types in the trachea, lung, intestine and kidney. Bat

201 exhibites more similar expression pattern to human in some organs (ACE2 and ANPEP4

202 in intestine epithelial cells; TMPRSS2 in lung epithelial cells), comparing to that in mouse

203 (Extended Data Fig. 2g). Although similar expression patterns were detected in bulk-seq

204 data at organ level, the differences of cell types among species revealed by single cell

205 data suggest bat as a better model for viral cross-species transmission research.

206 The other human viral receptor genes NCL, CD55, HSPG2, and PDGFRA, are

207 expressed in the epithelial cells in both the respiratory tract and intestine, the viral

208 tropism cell types (Extended Data Fig. 3). The transcripts of desmoglein 2 (DSG2), the

209 receptor of Adv, Fc fragment of IgG receptor and transporter (FCGRT), fusion receptor of

210 enterovirus B, are mainly expressed in epithelial cell and brush cell of the trachea,

211 ciliated cell of the lung, and enterocytes in the intestine. These findings provide insights

212 to understand the cellular tropism of respiratory tract and intestinal tract viruses

213 (Extended Data Fig. 3).

214 This analysis of cell type specific gene expression data suggests that the distribution

215 of viral entry receptor genes cannot explain the asymptomatic nature of viral infection in

216 bats, and nor can it be explained by differential gene expression in those cell types. The

217 molecular and cellular characteristics of the immune response in the bat were therefore

218 then analyzed.

219

220 The Adaptive Immune System: T and B cell clustering and analysis

221 Adaptive immunity in bats has been of great interest to understand their

222 asymptomatic infection status as “viral reservoirs”. At the single-cell level, we analyzed

223 the transcription features exhibited in immune cells. T cells differentially expressed CD3

224 genes in all organs are analyzed by using unsupervised clustering method implemented in

225 Scanpy37. A total of 13 stable clusters are obtained, and each with unique signature genes

226 (Extended Data Fig. 3a, 3b, Extended Data Fig. 4a-4c). In many organs, the number of

227 activated T cells is much more than naïve T cells, such as liver, lung, trachea, intestine,

228 pancreas, bladder, heart, kidney, and wing membrane (Extended Data Fig. 4d). Five

229 clusters (C7, C8, C9, C11, and C12) express CD8 genes, and seven clusters (C1‐C6, and

230 C13) are composed of a mixture of CD4+ and CD8+ T cells. Most of C1, C3, C4 and C6

231 cluster are CD4+ T cell, while most of C2, C5, and C13 are CD8+ T cells. Cluster 10 is

232 composed of CD3+CD4-CD8- T cells. Cells of C1_CD4TN and C2_CD8TN clusters

233 expressing “naïve” marker genes such as LEF1, CCR7, and TCF7 38are mostly from

234 spleen and bone marrow, respectively (Extended Data Fig. 4b, c, e). The cluster of

235 C3_TREG-like is characterized by the expression of the IL2RA and CCR8 genes,

236 commonly associated with regulatory T cells (TREG-like). However, the FOXP3 gene

237 shows no expression in the clustered cells. The C4_TCM cluster characterized by CCR7,

238 SELL, and GPR183 is composed of central memory T cells (TCM). The C5_TEM cluster is

239 closest to effector memory (TEM) T cells in many organs, in accordance with the

240 expression of CD44, CXCR3, GZMK, CCL5, CTSW and NKG7, and the lack of

241 expression of lymph node-homing receptors CCR7 and SELL. The C6_TEM/TH1-like

242 cluster characterized by IFNG, CXCR3, GZMK, and CD4, which mainly distributed in the

243 intestine, lung, and liver. The C7_TH17 cluster contains TH17 cells mainly in the trachea

244 and lung, with high level expression of IL23R and RORC genes. In addition to TEM cells,

245 recently activated effector memory or effector T cells (TEMRA) are also identified. The

246 C10_TEMRA differentially highly expressed effector molecules such as NKG7, ZNF683,

247 CTSW, CCL5, GZMA, XCL1, KLRG1, and TBX21. It has been reported that chemokines

248 XCL1 and CCL5 derived from NK cells recruit cDCs into the tumor microenvironment,

249 which are critical for antitumor immunity39, while KLRG1+TBX21+ T cells are

250 long-lived effector cells, which contribute to infection control (Fig. 3b, Extended Data

251 Fig. 4a-c).

high high 252 The cells in C8_ tissue-resident memory T (TRM)-GZMA , C9-TRM-ZNF683 ,

253 and C11_IEL clusters express the ITGAE gene, a known marker of TRM cells. They share

high 254 signature genes, such as TIMP1, RGS1, and FCER1G. The cells in C8_TRM-GZMA

255 are predominantly from the intestine and express cytotoxic molecules such as GZMA,

high 256 GNLY, PRF1, and CCL5. Most of the cells in C9_TRM-ZNF683 are from the liver,

257 which express higher levels of effector molecules such as ZNF683, NKG7, XCL1 and

258 CCL5, and interferon stimulating genes (ISGs), including IFNG and IRF7. The cells in

259 the C11_IEL cluster are detected exclusively in the wing membrane, which are

260 considered as intraepithelial lymphocytes (IEL) as they highly expressed natural killer

261 cell receptor genes, NCR1 and KLRB140. These cells also display overwhelmingly active

262 molecules CD4441, chemokine XCL1, and ISG CD9 (Fig. 3c, Extended Data Fig. 4e).

263 The C12_NKT-like cluster characterizes NK cell receptor genes, including KLRB1,

264 KLRD1, KLRF1, KLRG1, NCR1, and NCR3 genes. All the genes express overlapping

265 with the CD3 gene and the cluster is considered as NKT-like cells. The C12_ NKT-like

266 cluster is composed of three subsets and each subset expressed distinct high level genes

267 in different organs (Fig. 3d-3g). The subset-1 which highly express KLRG1, GZMA, and

268 ITGA4 is considered as long-lived effector NKT and contribute extensively to immune

269 surveillance42. The subset-2 highly expresses active gene CRTAM and CD69, peptidase

270 inhibitor gene (IP3), chemokine XCL1, and immediate early genes (IEGs), such as JUND,

271 NR4A1, and FOSB. IEGs are rapidly activated at the transcriptional level in the first

272 round of response to stimulation prior to any nascent protein synthesis. These data

273 suggest subset-2 NKT-like cells are in active states. The subset-3 NKT-like cells highly

274 express SCGB3A1, SCGB3A2, MAPT, GNLY, and BCL2. The SCGB3A1 is a tumor

275 suppressor gene, while SCGB3A2 is a negative inflammation response gene.

276 C13_proliferating T cells are significantly enriched in the expression of cell cycle genes

277 (Fig. 3f, Extended Data Fig. 4a-4c), such as MKI67, UBE2C, CENPF, PCLAF, TOP2A,

278 indicating the proliferative states of the C13 cells.

279 B cells are annotated into five clusters according to the marker genes (Fig. 3h, 3i).

280 C1 cluster contains activated B cells expressing high levels of CD86, CAPG, AHNAK,

281 ANXA2, and PHACTR1. C2 is defined as germinal center B (GC B) cell with the specific

282 expression of BCL-6, and cell cycle-related genes (MKI67, TOP2A, CENPF, CDCA3,

283 and CDKN3) C3 cluster is defined as marginal zone B (MZB) cell, which highly

284 expressed MZB1, DTX1, and NW_017739275.1:124060-124578 (corresponding to

285 Rousettus aegyptiacus complement component 3d receptor 2 (CR2) gene). Some MZB

286 cells express SDC1, indicating a conserved maturing location of plasma cells. The C4

287 cluster is characterized by higher expression of FABP4, RGS1, STAP1, and PIK3R1,

288 which are defined as naïve/memory B cells. The C5 cluster is annotated as long-lived

289 plasma cells, in which the transcription genes SDC1, PRDM1, and XBP1 and marker

290 genes SDC1 and TNFRSF17 expressed at a high level, while CD19 and MS4A1 were

291 under-expressed. A majority of B cells were in the spleen and adipose tissues (Fig. 3j).

292

293 The gene expression patterns of mononuclear phagocytes

294 Mononuclear phagocytes (MNPs) play a critical role in pathogen sensing,

295 phagocytosis, and antigen presentation. The MNPs in bat tissues are profiled and 12

296 clusters are grouped according to differentially expressed transcripts (Extended Data Fig.

297 5a, Supplementary Table 1). C9_granulocyte-monocyte progenitor (GMP) is identified in

298 bone marrow, with specific expression of CTSG, MPO, ELANE, and RTN3. Two clusters

299 of monocytes are identified, including C3-classical monocyte (cMo) and C1_nonclassical

300 monocyte (ncMo). Six clusters are macrophages, including C0_CSF3Rhigh macrophage

301 (CSF3Rhigh Mac), C10_CD300Ehigh macrophage (CD300Ehigh Mac), C2_Kuffer cells

302 (KC), C4_SPIChigh macrophage (SPIChigh Mac), C5_LYVE1high macrophage (LYVE1high

303 Mac), and C6_CCL26high macrophage (CCL26high Mac). The macrophage clusters are

304 characterized by unique expressed genes, such as CSF3R and SERPINA12 in CSF3Rhigh

305 Mac, CD300E and LPO in CD300Ehigh Mac, MARCO and CLEC4G in KC, CNTNAP2,

306 SPIC, and VCAM1 in SPIChigh Mac, LYVE1 and DAB2 in LYVE1high Mac, CCL26 and

307 SCD in CCL26high Mac (Extended Data Fig. 5b, Supplementary Table 1). KC, SPIChigh

308 Mac, LYVE1high Mac, and CCL26high Mac are tissue-resident macrophages with high

309 expression of C1QA, C1QB, C1QC, and MAFB. A total of about 600 differentially

310 expressed genes are identified in cross different tissue-resident macrophage populations.

311 The differential expressed genes in CSF3Rhigh Mac, mainly identified in the intestine, are

312 enriched in leukocyte migration, leukocyte chemotaxis, and positive regulation of

313 response to external stimulus in GO annotations (Extended Data Fig. 5c and 5d). SPIChigh

314 Mac mainly comes from the spleen. The enriched genes for GO annotations are mainly

315 responsible for signal transduction, activation of the immune response, and regulation of

316 monocyte chemotaxis. LYVE1high Mac contains many organs macrophages, such as the

317 bladder, pancreas, thymus, adipose tissue, heart, tongue, trachea, testis, kidney, lung,

318 muscle, and intestine. The enriched gene functions mainly include wound healing, cell

319 migration, and protein activation cascade. CCL26high Mac cluster contain macrophages of

320 the lung and trachea, which are mainly associated with lipid transport and metabolic

321 process, phagocytosis, and regulation of endocytosis (Extended Data Fig. 5c, d).

322 Four DCs subtypes are determined (Extended Data Fig. 5a). C7_cDC1 is

323 characterized by FLT3, CLEC9A, XCR1, IRF8, and CPVL. C12_pDCs highly express

324 TCF4, IRF8, IL3RA, IRF4, LAMP3, BCAS4, and GPM6B. C11 is annotated as activated

325 DCs, with high expression of DC hallmark receptor gene FLT3, activation marker gene

326 LAMP3, co-stimulatory molecule genes ICOSLG and CD83, and chemokine receptor

327 genes CCR7 and IL7R. C8_Langerhans cells (LCs) are mainly located in the wing

328 membranes, with highly expressed genes of FLT3, RUNX3, EPCAM, and TACSTD2

329 (Extended Data Fig. 5b, c). Collectively, monocytes, macrophages, and DCs display

330 distinct gene landscapes, which likely form the basis of MNPs specificity and plasticity.

331 The distinct gene profiles of MNPs may contribute to the critical role of MNPs in

332 pathogen sensing, phagocytosis, antigen presentation, tissue function and homeostasis.

333

334 Innate immunity: the response of bat primary lung fibroblast cells against RNA

335 virus infection

336 We then studied the innate immunity activities since it is the first-line to control the

337 virus infections. Real-time quantitative PCR analysis revealed that innate immunity

338 related genes, such as retinoic acid-inducible gene-I (RIG-I), melanoma

339 differentiation-associated protein 5 (MDA5), toll-like receptor (TLR) 3, TLR7-9,

340 interferon regulatory factor (IRF) 3, IRF7, IFNα, β, ω, and γ, are expressed in various

341 tissues (Extended Data Fig. 6). All of these genes are highly expressed in the spleen and

342 white adipose tissue. Furthermore, TLR3 and TLR7 are highly expressed in the intestine.

343 RIG-I, MDA-5, TLR-3, TLR-8 and IRF3 are highly expressed in the lung (Extended Data

344 Fig. 6).

345 To analyze the innate immune activities at the lung cellular level, we isolated

346 primary bat lung fibroblasts (BPFs). According to the transcriptomic data, the lung stomal

347 cells constitutively expressed innate immune genes (Extended Data Fig. 7). An RNA

348 virus, vesicular stomatitis virus (VSV), and/or the analogs stimulating the signaling

349 pathways, were used to treat BPFs and human primary lung fibroblasts (HPFs) (Fig. 4a).

350 The cells were stimulated with poly (I:C), R848, the analogs of RIG-I/MDA-5, TLR3,

351 and TLR7/8, respectively, as well as VSV. At 4 hours (h), 8h, 12h and 24 h after treatment,

352 the expression levels of RIG-I, MDA5, IFNα, β, IL-6 and TNFα were analyzed. In

353 HPF, the transfection of poly (I:C) induces the expression of IFNα, β about 4,000-fold

354 compared to untreated cells at 4h post-treatment, while the incubation of poly (I:C), for

355 the purpose of stimulating the TLR3 pathway showed similar results (Fig. 4c-4e).

356 However, the extent of IFN-β mRNA induction was much lower in BPFs when compared

357 with HPFs after 4h post-treatments (p=0.000, student t test). The transfection of R848

358 induces higher expression levels of IL-6 and TNFα mRNA in HPFs, but not in BPFs (Fig.

359 4b). Similar results were obtained in VSV-infected cells (Fig. 4f). Although the VSV

360 replicates in a low level in BPFs compared to that of HPFs, the mRNA levels of MDA-5

361 and RIG-I increased slightly. However, the transcription of IFN-β, IL-6, and TNF-α

362 does not increased significantly compared with that in HPFs.

363 364 Discussion

365 The single-cell transcriptome data obtained from the model organism mouse and

366 human has established a reference database in mammals for deep molecular annotation of

367 cell types13-15. Here, we have created a parallel cell atlas in an important organism

368 trapped from the wild.

369 Most emerging infectious diseases in humans are dominated by zoonoses43. Over

370 millions of years, bats have evolved a special ability to carry a variety of viruses but

371 show little or no signs of disease. However, many of these viruses result in devastating

372 infection when they cross the species barrier to humans44,45. Bats are social animals and

373 diverse viruses circulate within the colony, allowing them to be important natural viral

374 reservoirs45. Viral strains or mutatants adapted to human beings or other species may

375 occur during the circulation, which can spill over to human beings or other animal

376 species (intermediate species). This may result in epidemics or outbreaks in human

377 beings by bat-human or bat-intermediate hosts-human transmissions46. Therefore,

378 bat-borne viruses etiologically play a pivotal role in human emerging infectious diseases

379 (EIDs), and understandings in how bat carry and transmit viruses has become a priority

380 issue for the EIDs alert and prevention47,48. The infection and replication of viruses rely

381 on specific host cells due to their parasitic nature. Interactions between the virus and the

382 host affect the infections and the replicate abilities of the virus, and we have lacked an

383 understanding of how host cell biology determines whether the infection is asymptomatic

384 or pathogenic. Furthermore, the pathogen’s shedding route is highly dependent on the

385 replication tissue sites. However, the lack of precise annotation of cellular composition of

386 bat organs/tissues has hindered the understanding on the many key aspects of zoonotic

387 virus origin in bats, e.g. the mechanisms of asymptomatic bearing of diverse viruses,

388 tropism and tissue targeting, virus shedding route and interspecies transmission, etc. It is

389 critically needed to elucidate the cellular composition as well as their functions and

390 interplay in various bat organs/tissues. However, it is still hard to create bat cell atlas by

391 conventional immunological or histological approaches due to the lack of sufficient

392 antibody reagents at present. Single-cell sequencing does not rely on cell surface protein

393 markers and antibodies. By clustering based on the transcription characteristics and

394 specifically transcribed genes, cells in organ/tissues can be classified by sc-seq. In this

395 study, we developed the first bat cell atlas by single-cell RNA-seq, which provides a

396 powerful tool for in-depth understanding of the cellular mechanisms by which how bats

397 carry, shed and cross-species transmit viruses.

398 Binding and entry into the host cell is the first step of virus infection. The specific

399 receptor molecules on host cell membranes govern whether a virus can enter and infect

400 the cells. The bat-borne viruses, such as SARS-CoV, MERS-CoV, HeV, NiV, RABV,

401 EBOV, and MARV, have emerged for more than twenty years and resulted in human

402 infections in the world. A crucial factor for these viruses infected human is that these

403 viruses could enter the human cells through specific receptors. In this study, it was found

404 that bat-borne viruses share similar receptor distributions and expression in bat and

405 human. For example, the the NPC1 (receptor of EBOV and MARV) are distributed in

406 most organs in bat and human, with similar expression levels. It has been reported that

407 patients succumbed to EBOV and MARV infections have extensive necrosis in

408 parenchymal cells of many organs, including liver, spleen, kidney, and gonads49, which is

409 consistent with the distribution of receptors in bat in this study. Further, EBOV and

410 MARV have a broad cell tropism. It has been verified from fatal human cases or

411 experimentally infected nonhuman primates that EBOV and MARV could infect and

412 replicate in monocytes, macrophages, dendritic cells, endothelial cells, fibroblasts,

413 hepatocytes, and several types of epithelial cells20,50. The distributions of NPC1 in

414 immune cells and nonimmune cells further support the broad cell tropism of EBOV and

415 MARV. ACE2, the SARS-CoV and SARS-CoV-2 receptor, is expressed in epithelial cells

416 of the lung and the small intestine, which are the primary targets of the two CoVs, as well

417 as in the heart, kidney, and other tissues16,51. In this bat data, it was found that ACE2 is

418 mainly expressed in different epithelial cells of the intestine, lung and trachea, such as

419 enterocytes, enteroendocrine cells, goblet cells and tuft cells, and lung and trachea

420 ciliated cells. TMPRSS2 showes higher expression in enterocyte of the intestine, AT1 in

421 the lung and collecting duct cells in the kidney. However, most of the receptor genes of

422 respiratory viruses show a higher expression level in bat intestine epithelial cells.

423 Previous studies also showed that SL-CoVs are majorly detected in the intestine of bats3,4.

424 These findings indicate that intestine is probably a major site where many viruses reside

425 and replicate, such as SL-CoVs4,7. This may facilitate their dispersal in the nature as feces

426 harboring the shed viruses can touch other animal species more effectively than the

427 respiratory route. These data suggest that the similar receptor distribution patterns

428 between bat and human may be one of the bases of cross-species spread of bat borne

429 viruses. Further, some virus receptors, such as SARS-CoV, SARS-CoV-2, MERS-CoV,

430 HeV, NiV, RABV, EBOV, and MARV, are also co-located in the lung, bladder, and

431 intestine of both species, which is critical in virus transmission. The clarifications on the

432 consistence and difference of surface molecular patterns between bat and human across

433 cell types, for example, the viral receptor gene, would be informative to assess the

434 cross-species transmission risk of bat borne viruses.

435 The knowledge of cellular immunity of bats is quite limited. According to the sc-seq

436 data, we found that CD8+ T cells were predominant over CD4+ T cell in Chinese

437 horseshoe bats (Rhinolophus sinicus). All tissue-resident memory T cells, including

high high + 438 C8-TRM-GZMA , C9-TRM-ZNF683 , and C11_IEL, are CD8 T cells. These TRM

439 cells highly expressed many effector molecules such as GZMA, GNLY, PRF1, ZNF683,

440 NKG7, XCL1 and CCL5, and so forth. Microbes most often attack body surfaces and

441 mucosal sites. TRM cells lie in frontline sites of infection and need not proliferate. They

442 are anatomically positioned to respond most immediately, which contribute to pathogen

443 control after the initial infection. In addition to TRM cells, most of TEM and NKT-like cells

444 are CD8+ T cells, and they express many effector molecules and IEGs. Specifically,

445 subset-2 NKT-like cells highly expressed IEGs, which can induce a rapid response to

446 stimuli before new protein synthesis. At the same time, CD69, an activation inducer

447 molecule, displayes high enrichment in subset-2 NKT-like cells. These data imply an

448 active state of the NKT-like cells in subset-2. Collectively, these predominant CD8+ T

449 cell and their functional states suggest that the immune baseline level of the bat is quite

450 high and is geared towards fighting microbe infections. The resident tissue CD8+T cells

451 and NKT-like cells with the higher expression level of immediate early genes indicates

452 effective cellular immunity response restricting viral infections in bats.

453 It has been reported that KLRG1+ T cells and NKT are long-lived effectors and

454 optimally provide immediate protective immunity against certain pathogens42,52. In this

455 study, subset-1 NKT-like cells display high expression of KLRG1, with co-expressed

456 ITGA4 and GZMA. These NKT-like cells distribute in different tissues of the bat. This

457 will help the bat to better conduct immune surveillance and fight against infections and

458 tumors. TEMRA cells present high expression of KLRG1 and TBX21 in the bat, which have

459 been reported to be expanded and maintained long term following boosting, without

52 460 losing their protective superiority . TRM cells resident in the local environment long after

461 peripheral infections subside. If an infection is localized to peripheral or extralymphoid

462 compartments, TRM cells would provide superior immune protection than circulating

463 memory T cells53. The circulating CD8+ memory T cells is failed to control the wing

464 membrane infection with HSV, while the TRM cells in the wing membrane provide local

465 protection against infection in the absence of ongoing T-cell stimulation. We found that

466 there are many TRM cells in the bat intestine, liver, and wing membrane, indicating an

467 activated adaptive immunity, which may offer effective barrier immune protection for

468 bat.

469 The highly activated cellular immunity may protect bats from viral damage. But how

470 can the virus reside and replicate in bats? The tolerance of viral infections in bats appears

471 to involve a balance between viral clearance and host tissue damage promoted by

472 proinflammatory effectors. The innate immune system is the first defense against

473 invading pathogens in mammals and type I IFNs are induced very early in viral infection.

474 The magnitude and nature of the IFN response determines whether the resulting effects

475 on the host are harmful or beneficial54. In Chinese horseshoe bats (Rhinolophus sinicus),

476 the IFN gene loci are still not clarified clearly. However, the critical components of the

477 IFN signaling pathway have been investigated55,56. For example, the sequences of RIG-I,

478 STAT-1 and IFN-β have close homology with human, mouse, pig and rhesus monkey in

479 immortalized embryonic fibroblast (BEF) cell lines from Rhinolophus affinis and

480 Rhinolophus sinicus57. Our data show that the critical host genes in the IFN signaling

481 pathways are expressed across the cell types. To characterize the innate immunity in bat,

482 we isolated BPFs from one of the Chinese horseshoe bat (Rhinolophus sinicus) lungs. We

483 found that the induction of most major pathogen associated recognition pattern (PAMP)

484 receptors, including RIG-I, TLR-3, and TLR7/8 as well as IFN-β and proinflammatory

485 factors, such as IL-6 and TNFα, are very low in BPFs compared to HPFs when stimulated

486 by polyI:C and VSV. These data indicated that the signaling pathways of innate immunity

487 in bat are tightly suppressed. The low level innate immune response may enable the bats

488 to asymptomatically harbor viruses.

489 In conclusion, we show here a first comprehensive bat cell atlas based on single-cell

490 transcriptional landscape of 19 organs from Chinese horseshoe bat. By combining the

491 sc-seq and bulk-seq data, we characterized the distribution patterns of multiple known

492 human viral receptors in bat and human across organs and cell types. We also

493 demonstrate an orchestration of highly activated adaptive immunity and suppressed

494 innate immunity status, which may form a precise immune hemostasis which allow the

495 virus harbor in bats without pathological damage. Our findings provide insights into the

496 cellular mechanisms to enable bats to serve as natural viral reservoirs, largely informing

497 an active alert and control of epidemics caused by bat borne viruses.

498

499 Online content

500 The methods, additional references, source data, statements of data availability and

501 associated accession codes are available online.

502

503 Methods

504 Bat, organs and single cell preparation

505 The two male Chinese horseshoe bat (Rhinolophus sinicus) were obtained in

506 October, 2018 from Anhui province, China. The bats were placed separately and

507 transferred to the lab. The species of each bat was identified by field biologists and

508 recorded. After anaesthetization with pentobarbital sodium (75mg/kg), bats blood was

509 drawn via cardiac puncture using sterile syringes, then the other organs and tissues were

510 isolated as followed, pancreas, intestine, spleen, liver, kidney, brown adipose tissue

511 (interscapular adipose tissue), white adipose tissue (visceral and subcutaneous adipose

512 tissue), thymus, heart, lung, trachea, bladder, testis, tongue, brain, muscle, wing

513 membrane, and bone marrow (forelimb bones). The cell suspensions from each tissue and

514 organ were prepared and the details were available as followed. The experiments and

515 programs were reviewed and approved by the Institutional Animal Care and Use

516 Committee of the Institute of Laboratory Animal Science, Peking Union Medical College

517 (BYS18003).

518 Single cell preparations.

519 The whole blood was quickly transferred into 1.5ml sterile tubes with anticoagulant

520 EDTA and mixed gently, then suspended with 0.5 ml of red blood cell lysis buffer. Cell

521 suspension was incubated on ice for 1 min and lysis reaction was quenched by adding 10

522 ml Dulbecco's Phosphate Buffered Saline (DPBS) with 2 mM EDTA and 0.5% BSA.

523 Cells were collected at 200g× for 5 min at 4 and washed with DPBS for two times to

524 remove the lysis buffer. The viability of cells was determined with trypan blue stain

525 method by calculating the rate of bright cells (viable) to stained cells (no-viable) with

526 hemocytometer.

527 Spleens were rinsed and dissected quickly in cold DPBS, then squeezed to pass

528 through a 70 μm strainer using plungers. Cells were collected into a 50ml centrifuge tube,

529 and then centrifuged at 300 g× for 5 min at 4. Cells were resuspended with 3 mL of red

530 blood cell lysis buffer. Cell suspension was incubated on ice for 1 min and lysis reaction

531 was quenched by adding 20 ml DPBS with 2 mM EDTA and 0.5%BSA. Cells were

532 collected at 300g× for 5 min at 4 and washed for 2 times with DPBS, then counted

533 with hemocytometer after Trypan blue staining as described above.

534 Bone marrow was isolated from bat forelimb bones. Both ends of bones were

535 carefully trimmed to expose the interior marrow shaft after removed the wing membrane

536 and muscles. The bone marrow cells were flushed by using 1 ml syringe with DPBS for

537 several times, all the cells were collected into a 70 μm strainer hanging on a 50 ml

538 centrifuge tube. Bone marrow cells on the strainer were gently squeezed to pass through

539 by using plungers. Cells were centrifuged at 200 g for 5 min at 4 and resuspended with

540 red blood cell lysis buffer. The red blood cell lysis, washing, and cell counting process

541 were similar as above.

542 Other organs were minced into pieces on ice with sterile scissors respectively. Tissue

543 pieces were respectively transferred into a 15 ml centrifuge tube and suspended with 5 ml

544 of enzymatic digestion buffer. Samples were treated with different enzymes formula. The

545 bladder, brain, brown and white adipose tissue, intestine, liver, lung, pancreas, testis,

546 thymus, and trachea were respectively digested in enzymatic digestion buffer with

547 0.4mg/ml collagenase IV, 0.4mg/ml collagenase/dispase, 30U/ml DNase, 0.5% BSA in

548 HBSS, at 37, 100rpm for 30min. Heart was digested with 1mg/ml collagenase/dispase,

549 30U/ml DNase, 0.5% BSA in HBSS at 37, 100rpm for 45min. The intestine, muscle

550 and testis were digested in enzymatic digestion buffer with 0.4mg/ml collagenase II,

551 30U/ml DNase,0.5% BSA in HBSS, at 37, 100rpm for 60min. The kidneys and wing

552 membrane were digested with 0.25% Trypsin and 30U/ml DNase, at 37 for 15min and

553 30min, respectively. Tongue was digested with 0.4mg/ml collagenase IV, 30U/ml DNase,

554 0.5% BSA in HBSS, at 37, 100rpm for 60min. Tissue pieces were pipetted up and

555 down gently for several times to dissociate into single cells during digestion. After

556 passing through a 70 mm strainer, the dissociated cells were centrifuged at 300 g for 5

557 min at 4 and treated with red blood cell lysis procedure. All the treated cells were

558 finally diluted to a density of 1000 cells/μl in DPBS with 0.4% BSA.

559 Single-cell sequencing library construction and sequencing

560 Sc-seq libraries were constructed by using the Single-Cell Instrument (10

561 ×Genomics, Pleasanton, CA) with Chromium v2 single cell 3’ library and gel bead kit V2

562 (10 × Genomics, Pleasanton, CA). In brief, cell suspensions were diluted in DPBS with

563 0.04% BSA to concentration of 1,000 cells/μl and the concentration was measured with

564 haemocytometer. The volume of single cell suspension required to generate 4,000 single

565 cell gel beads in emulsion (GEMs) was loaded into a separate channel on the Single Cell

566 3′ Chip. The final libraries were qualified with Agilent 2100 Bioanalyzer (Agilent

567 Technologies, Santa Clara, CA, USA), and quantified by qPCR with the quantification kit

568 (Tian Gen company, China) for Illumina with QuantStudio 12K Flex Real-time PCR

569 system (Thermo Fisher Scientific, Waltham, MA, USA). Libraries were diluted to 2 nM

570 in each and pooled with equal volume before sequenced on Hiseq X Ten (Illumina, Inc.,

571 San Diego, CA, USA) with 150-bp pair-end strategies.

572 Bulk RNA-seq library construction and sequencing

573 Approximately 30-50 mg of each tissue was collected from each bat and

574 homogenized using FastPrep-24 system (MP Biomedicals, France) in 1ml of TRIzol

575 (Invitrogen, Carlsbad, CA). RNA was then extracted following standard protocol. The

576 RNA qualities determined by RNA Integrity Number (RIN) were assessed on an Agilent

577 Bioanalyzer RNA 6000 nano chip (Agilent Technologies, Santa Clara, CA, USA). The

578 libraries were constructed by using the NEBNext ultra II RNA library prep kit (New

579 England BioLabs, Ltd., USA) and the qualities were analyzed with Agilent 2100

580 Bioanalyzer (Agilent, Santa Clara, CA). Libraries were then sequenced on HiSeq X Ten

581 (Illumina) with 150-bp pair-end strategies.

582 Single cell sequencing data processing and clustering

583 Sequencing reads were first aligned to Rhinolophus sinicus genome

584 (GCA_001888835.1) using CellRanger (version 3.0.0, 10× Genomics) with default

585 parameters. Then the sequencing data was processed for filtering, variable gene selection,

586 dimensionality reduction, and clustering by using Scanpy package (version 1.3.7). Cells

587 with fewer than 500 detected genes were excluded, as well as expressed fewer than 1,000

588 unique molecular identifiers (UMIs). Gene expressions were normalized as divided by

589 total UMIs of each cell and multiplied by 10,000. Highly variable genes were selected by

590 coefficient of variation with cutoff of 0.5. After log-normalized and scale, the data

591 dimensionality was reduced by principal component analysis (PCA) by variable genes.

592 Neighborhood graph of observations were computed based on the Euclidean distance and

593 parameters were adjusted for each tissue. The Batch balanced KNN package (bbknn,

594 version 1.3.1) was used for batch correcting followed the procedure by identifying the K

595 nearest neighbours for each individual cell. Cluster cells using the Leiden algorithm and

596 cell type of each cluster was determined by using the abundance of known marker genes.

597 Cells were visualized using UMAP method which is a manifold learning technique

598 suitable for visualizing high-dimensional data. To compare the human and mouse gene

599 expression with the bat respectively, we use the public databases of human metadata

600 available on GEO (accession GSE130148) and mouse metadata online

601 (http://tabula-muris.ds.czbiohub.org/) for later normalization and gene expression

602 comparison.

603 Bulk sequencing data processing

604 The gene expression profiles of bat tissues from bulk-seq data were performed

605 following typical RNA-Seq procedure with reference genome. The raw-reads were

606 treated to generate clean-read datasets by the following procedure. Reads with adaptors

607 or containing unknown nucleotides more than 5% were removed directly. The

608 low-quality reads containing more than 20% suspect-nucleotides of Phred Quality Score

609 less than 10 were then filtered out. The qualified reads were evaluated to trim unreliable

610 ends containing more than 3 successive suspect-nucleotides. Clean-reads were mapped to

611 Rhinolophus sinicus genome by hisat2. Read counts of each gene were calculated by

612 stringtie and prepDE.py scripts. The count matrix was then processed by DESeq2 for

613 normalization and expression profiles.

614 Gene Ontology (GO) analysis

615 Differential genes were obtained by comparing the each macrophage cluster with

616 others, than the genes were used for analysis with p-adjust value＜0.05, mean expression

617 value >1. The differential expression more than two times were further performed Gene

618 ontology (GO) analysis using clusterprofiler package58 with mouse database

619 (org.Mm.eg.db). A P value ≤0.05 was considered significant and enriched GO terms were

620 sorted by counts. A column chart was plotted using top 10 GO terms.

621 Comparative analysis of gene profiles in bulk and single-cell sequencing

622 The characteristics genes in each tissue were selected from bulk-seq data if their

623 expression level were more than 50, and 10-fold higher than other tissues. Heat-map was

624 made by Seaborn package (0.9.0), showing the genes expression level in selected tissue

625 compared to the average of level in all tissues. These genes were than analyzed in

626 single-cell sequencing data to decide the distribution in each tissue by average

627 expression.

628 To compare the human and mouse gene expression with the bat respectively, we use

629 the public databases of human metadata available on GEO (accession GSE130148,

630 GSE134355) and mouse metadata online (http://tabula-muris.ds.czbiohub.org/) for later

631 normalization and gene expression comparison.

632 Correlations of cell type specific transcription genes

633 After the decision of cell types with significant transcription genes (average

634 difference of > 1), the average gene transcription factor sets that distinguish each

635 individual cell type from all other cells was calculated. The pearson’s correlations of

636 specific cell types were analyzed with corr imbed in pandas package (version 0.23.4).

637 T cells analysis

638 T cells analysis was performed by involved all organs. The differential analysis of

639 each organ was performed, and the gene with log2 fold change ≥2 and pval_adj <1 was

640 extracted. PCA is used for dimensionality reduction of T cells data. And then T cells

641 were clustered by using leiden model, and reduced-dimensional mapping by using umap.

642 Amino acid identity of viral receptor genes

643 To analyze the identity of viral receptor genes, all related coding sequences were

644 downloaded from Ensembl and GenBank representing human, bats and mouse. The

645 sequences were manual checked to avoid false annotation or different isoforms, then

646 ClustalW Multiple alignment in BioEdit version 7.0.5.3 was used for amino acids

647 sequence alignment between Chines horseshoe bat (Rhinolophus sinicus) and the other

648 species.

649 Single-molecule fluorescent in situ hybridization

650 Probe libraries were custom designed and constructed by Advanced Cell Diagnostics

651 (ACD, Newark, CA) for bat SFTPC and CLDN5. The single molecule FISH probe

652 libraries consisted of 20 probes with length of 50 bps. The probe libraries of SFTPC and

653 CLDN5 were respectively coupled to HRP-C1 and HRP-C2, then stained with OpalTM

654 fluorescent reagents. The single cells were washed with DPBS, fixed in 10% neutral

655 formalin buffer for 1h at 37 , then centrifuged at 250×g for 10 min and resuspended in

656 70% ethanol for incubating at RT for 10 min and stored at 4°C. Adjust the cell density to

657 1×106 cells/ml. Cell suspension droplets were added onto the slices and dried, then

658 incubated in 50% ethanol, 70% ethanol and 100% ethanol, for 5min at each step. The

659 slices were dried at 37°C for 30 min, then draw for 2- 4 times around the cell spot by

660 using the hydrophobic barrier pen. The probes hybridizing was performed in accordance

661 with the manufacturer’s instructions by using RNAscope® Multiplex Fluorescent

662 Reagent Kit v2 and hybridization oven (HybEZ™, ACD, Newark, CA). The cells were

663 incubated with the Hybridize Probes, hybridize Amp 1, Amp 2 and Amp 3 at 40 for 2h,

664 30min, and 15min, respectively, then incubated with horseradish peroxidase (HRP)-C1

665 and HRP-C2. The nucleus was stained with DAPI (Invitrogen, Waltham, MA, USA) for

666 30 second and ProLong™ Gold antifade reagent was placed on the slices. Images were

667 taken by using Vectra Polaris Automated Quantitative Pathology Imaging System

668 (PerkinElmer, Waltham, MA, USA).

669 Cell culture.

670 Primary bat pulmonary fibroblast (BPF) cells were cultured from one lung of the

671 Chinese horseshoe bat (Rhinolophus sinicus). The lung was pretreated followed the same

672 procedure of single cell preparation. The cells were suspended in Roswell Park Memorial

673 Institute (RPMI) 1640 medium (Thermo Fisher Scientific, CA, USA) containing 10%

674 fetal bovine serum (FBS) (Hyclone, Logan, UT, USA) and 1% penicillin (10,000 IU)

675 -streptomycin (10,000μg/mL) (PS) (Thermo Fisher Scientific, CA, USA), then cultured

676 in a 24-well culture plate for 48 h until the fibroblasts attached to the bottom of the plate.

677 Then the culture medium was replaced by Fibroblast Medium (ScienCell, Carlsbad, CA,

678 USA) containing 2% FBS and 1% PS. The BPF cells were tested by mycoplasm

679 detection kit (Lonza, Walkersville, MD, USA). The cell type was confirmed by in situ

680 hybridization using RNAscope® Probes (ACD) targeted to fibronectin 1 (FN1) and

681 asporin (ASPN) genes.

682 Cell lines and viruses

683 Human Pulmonary Fibroblasts (HPFs, ScienCell, Carlsbad, CA, USA) are

684 characterized by immunofluorescence with antibody specific to fibronectin (Santa Cruz,

685 CA, USA) and Alexa Fluor 488-ligated second antibody (ZSGB-BIO, China). HPFs were

686 cultured in Fibroblast Medium (ScienCell). Vesicular Stomatitis Virus (VSV) was stored

687 in our lab and the viral titer was 5.25×109 plaque forming unit (PFU) /ml.

688 Quantitative reverse transcription PCR (qRT-PCR)

689 BPFs and HPFs were cultured in 12-well plate (2.5×105 cells/well) and transfected with

690 1μg poly (I:C) (InvivoGen, CA, USA) or 2 μg ISD (InvivoGen, CA, USA) by

691 lipofectamine 2000 reagent (Thermo Fisher Scientific, CA, USA), the culture medium

692 was replaced with Opti-MEM™ Reduced Serum Medium (Thermo Fisher Scientific, NY,

693 USA) after 4h transfection, and the cells were collected at 4 h, 8h, 12h and 24h post

694 transfection. BPFs and HPFs were also stimulated with 10 μg/ml of poly (I:C) or 2μg/ml

695 of R848 (MCE, NJ, USA), or medium as control. Poly (I:C) low molecular weight (LMW)

696 and high molecular weight (HMW) (InvivoGen, CA, USA) were used initially and they

697 would stimulate the signaling pathway in the two cells. Then the poly (I:C) HMW was

698 then used furtherly. For VSV infection, both cells were infected with VSV at MOI of 0.5.

699 The cells in each well were collected at 4 h, 8h, 12h and 24h post stimulation or infection.

700 RNA was isolated as described above. Total 500 ng RNA was used to synthesize cDNA

701 by using Moloney-murine leukemia virus (M-MLV) reverse transcriptase (Promega,

702 Madison, WI). Diluted cDNA was used in each quantitative reverse transcription-PCR

703 (qRT-PCR). Primers used in qRT-PCR were listed in Supplementary material. The

704 qRT-PCR was performed by using Bio-rad with real-time CFX96 amplifier

705 (Bio-Rad Laboratories, Inc., USA) using the TB GreeenTM Premix Ex TaqTM (TaKaRa,

706 Japan). The primers targeted to human and bat IFNβ, IL-6, TNFα, RIG-I and MDA5

ΔΔ 707 were used. Fold change expression of genes were calculated by CT method. The mean

708 value was from three replicates, and error bars represent standard deviations.

709 Data availability

710 All gene expression data from single cell and bulk sequencing have deposited in the

711 Genome Sequence Archive (GPB 2017) in National Genomics Data Center (NAR 2020),

712 under project that is publicly accessible at https://bigd.big.ac.cn/gsa.

713

714 Acknowledgments

715 We thank Dr. Zhuo Zhou (Peking University, Beijing, China) give us valuable

716 suggestion to improve the paper. This study was funded in part by the Chinese Academy

717 of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2016-I2M-1-014,

718 2019-I2M-2-001), the National Major Science & Technology Project for Control and

719 Prevention of Major Infectious Diseases in China (2017ZX10103004), the Non-profit

720 Central Research Institute Fund of CAMS (2019PT310029), the Ministry of Science and

721 Technology of China (2018YFA0108100), the National Natural Science Foundation of

722 China (21525521, 21927802), Beijing Advanced Innovation Center for Genomics, and

723 2018 Beijing Brain Initiative (Z181100001518004).

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897 JWW, JBW, YYH, and LLR conceived and designed experiments. CHW, YX, LLH,

898 ZQW and XX performed the experiments. CW, JCY, LLR, AOP, LG, JBW, YYH, HPW,

899 LLH, HZ, CHW, YWL, JCZ, LSS, MKL and XBL analyzed the data. LLR, LG, CHW,

900 YYH, JBW, SRQ and JWW wrote the manuscript. All authors reviewed the manuscript.

901 Conflict of Interest Disclosures

902 All authors declare no competing interests.

903 Role of the Funder/Sponsor

904 The funders had no role in the design and conduct of the study; collection,

905 management, analysis, and interpretation of the data; preparation, review, or approval of

906 the manuscript; and decision to submit the manuscript for publication.

907 Figure legend

908 Figure 1. Overview of Chinese horseshoe bat cell atlas. a, Work flow of single cell

909 sequencing. Cells from two male bat organs were processed for transcriptomic

910 amplification, sequencing and data analyzing. b, The expression level of viral receptor

911 genes across organs based on bulk-seq data between bat, human and mouse. The size of

912 circle represents the gene expression level and the colors showed the species. c, Axis on

913 the triangular representation of the distributions of viral receptor genes across the organs

914 in bat, human and mouse. The size of the signals represents the mean gene expression

915 showed as ln (expression + 1). d, UMAP plots of all cells, colored by organ, overlaid

916 with the predominant cell type composing each cluster, n = 82,924 individual cells. e,

917 The number of annotated cell types in each organ.

918

919 Figure 2. Differential expressions of bat lung cells compared to human and mouse,

920 and the distribution of viral receptor genes across cell types. a, UMAP visualization

921 and marker-based annotation of lung cells. Cells are colored by cell-type. b, Comparisons

922 of the differential genes expressed in endothelial cells, epithelia cells, mesenchymal cells,

923 and immune cells in bat compared to that of human and mouse. Differential expressed

924 genes with p-adjust<=0.05 were analyzed. Results are visualized by heatmaps of

925 normalized gene expression and histograms of fold change between cell types. c, Violin

926 plots of viral receptor genes expression in top 5 cell types.

927

928 Figure 3. Analysis of bat T and B cells.

929 a, UMAP visualization of all T cells from Chinese horseshoe bats (Rhinolophus sinicus),

930 showing the formation of 13 main clusters shown in different colors. The functional

931 description of each cluster is determined by the gene expression characteristics of each

932 cluster. n = 9,663 individual cells. b, Violin plots showing the enriched transcripts of

933 different T cell clusters. c, Violin plots showing the enriched transcripts of

high high 934 TRM-GZMA , TRM-ZNF683 , and IEL. d, UMAP visualization of NKT-like-1,

935 NKT-like-2, and NKT-like-3 cells. Colors indicate different organs, and shapes indicate

936 cell types. e, UMAP plots showing expression of selected long-lived effector genes and

937 immediate early genes (IEGs) in this dataset. f, Violin plots showing the enriched

938 transcripts of NKT-like-1, NKT-like-2, and NKT-like-3 cells. g, Tissue preference of

939 each NKT-like cell cluster estimated by proportion. h, UMAP visualization of B cells

940 from Chinese horseshoe bats (Rhinolophus sinicus), showing the formation of 10 main

941 clusters shown in different organs. The functional description of each cluster is

942 determined by the differential expressed genes. i, Dot plot visualization of selected

943 marker gene for each cell type. The size of the dot encodes the percentage of cells within

944 a cell type in which that marker gene was detected, and the color encodes the average

945 expression level. j, Distribution of B cell types in different organs.

946

947 Figure 4. Expression levels of type I interferon in bat primary lung fibroblast. a,

948 Work flow of bat pulmonary primary fibroblast isolation. b, Cell type confirmation by

949 single-molecule fluorescence in situ hybridization with fibronectin 1 RNA probe. c,

950 Expressions levels of MDA5, RIG-I, IFNβ after the transfection of poly (I:C). d,

951 Expressions levels of IL-6, TNFα after the transfection of B848. e, Expressions levels of

952 IL-6 and IFNβ after the inoculations of poly (I:C). f, Expressions levels of MDA5, RIG-I,

953 IFNβ, IL-6, and TNFα after the infection of vesicular stomatitis virus (VSV). Error bars

954 represent standard deviation.

955

956

957 Extended Data

958 Extended Data Figure 1. Transcriptomic analysis by bulk sequencing and the

959 comparisons to single cell sequencing. a, Expression level of selected viral receptor

960 genes in organs based on bulk-seq data of bat and human. Adv: Adenovirus; RSV:

961 Respiratory syncytial virus; MV: measles virus; CAV: Coxsackie virus; CAV-A9:

962 Coxsackie virus A9; CAV-A16: Coxsackie virus A16; CAV-A13/18/21: Coxsackie virus

963 A13/18/21; HRV: Rhinovirus; EchoV: Echovirus; DENV: Dengue virus; EV-B:

964 Enterovirus B; HSV-1:Herpes simplex virus; HCMV: human cytomegalovirus; VZV:

965 Varicella zoster virus; VSV: Vesicular stomatitis virus. b, Histogram of the number of

966 detected genes (left) and UMIs (right) per cell for each organ. c, Dot plot visualization of

967 differentially expressed genes across clustered cells. d, The comparison of differential

968 transcriptional genes between bulk-seq and single cell (sc)-seq data in each organ.

969

970 Extended Data Figure 2. Analysis of the cell types and receptor genes distribution

971 patterns in single cell level. a, UMAP plots of expression for genes specifically

972 expressed in particular cell types (SFTPC in AT2 and CLDN5 in endothelial cells). Gene

973 expression levels are indicated by shades of red. b, Single-molecule fluorescence in situ

974 hybridization of SFTPC (Opal 520) and CLDN5 (Opal 690) on lung single cells droplet

975 slices. c, Dot plot visualization of selected marker genes for each cell type. The size of

976 the dot encodes the percentage of cells within a cell type in which that marker was

977 detected, and the color encodes the average expression level. d, UMAP visualization and

978 marker-based annotation of trachea cells. Cells are colored by cell-type. e, UMAP

979 visualization and marker-based annotation of kidney cells. Cells are colored by cell-type.

980 f, UMAP visualization and marker-based annotation of intestine cells. Cells are colored

981 by cell-type. g, Comparisons of the expression patterns of the respiratory virus receptor

982 genes, ACE2, DPP4, ANPEP, CXADR and the TMPRSS2 in endothelial cells, epithelia

983 cells, and mesenchymal cells in single cell levels in bat compared to that of human and

984 mouse. Only epithelial cells in intestine and kidney were selected for the comparisons

985 according to the available data. SARS-CoV, Severe acute respiratory syncytial virus;

986 HCoV, Human coronavirus; Adv: Adenovirus; CAV: Coxsackie virus.

987

988 Extended Data Figure 3. The known human viral receptors genes expressed in bat

989 across the cell types. Dot plots of expression for viral receptor genes in featured cell

990 types. The size of the dot encodes the percentage of cells within a cell type in which that

991 marker was detected, and the color encodes the average expression level.

992

993 Extended Data Figure 4. Summary of functional properties of various T cell clusters.

994 a, Heatmap of unique signature genes for thirteen T cell clusters. Selective specifically

995 expressed genes are marked alongside. b, UMAP plots of expression levels of selected

996 genes in different clusters indicated by the colored oval corresponding to Figure 3a. c,

997 Overview of T cell cluster characteristics. d, The number of activated T cells and naïve T

998 cells in different tissue.

999

1000 Extended Data Figure 5. Analysis of mononuclear phagocytes. a, UMAP visualization

1001 of mononuclear phagocytes from Chinese horseshoe bats (Rhinolophus sinicus), showing

1002 the formation of 13 main clusters shown in different organs. The functional description of

1003 each cluster is determined by the gene expression characteristics of each cluster. b, Dot

1004 plot visualization of each cell type and selected marker gene. The size of the dot encodes

1005 the percentage of cells within a cell type in which that marker was detected, and the color

1006 encodes the average expression level. c, Tissue preference of mononuclear phagocytes

1007 estimated by proportion based on 10x data.d, Gene ontology analysis of macrophage with

1008 high expressions of CCL26, CD300, CSF1R, LYVE1 and SPIC.

1009

1010 Extended Data Figure 6. Analysis of innate immune gene mRNA expression in

1011 Chinese horseshoe bat tissues. Tissue mRNA expression levels of RIG-I, MDA5, TLR3,

1012 TLR7, TLR8, TLR9, IRF3, IRF7, IFNα, IFNβ, IFNω and IFNr were determined by

1013 qRT-PCR and normalised relative to GAPDH. Error bars represent standard deviation.

1014

1015 Extended Data Figure 7. Heatmap of innate immune response genes expression in

1016 lung epithelial cells, endothelial cells and stromal cells.

1017 1018 1019 1020

1021 Supplementary Material

1022 KEY RESOURCES TABLE

REAGENT or RESOURCE SOURCE IDENTIFIER

Cell Lines

Human Pulmonary Fibroblasts ScienCell, CA, USA Cat# 3300

Critical Commercial Assays

RNAscope® Probe-Rs-SFTPC-C1 ACD, CA, USA Cat# 583421

RNAscope® ACD, CA, USA Cat# 583431-C2

Probe-Rs-CLDN5-C2

RNAscope® 2-plex Negative ACD, CA, USA Cat# 320751

Control Probe

RNAscope® Multiplex ACD, CA, USA Cat# 323100

Fluorescent Reagent Kit v2

RNAscope® Probe-Rs-SFTPC-C1 ACD, CA, USA Cat# 583421

RNAscope® Probe-Rsi-ASPN ACD, CA, USA Cat# 826121

RNAscope® Probe-Rsi-FN1-C2 ACD, CA, USA Cat# 826111-C2

RNAscope® Probe-Rsi-AQP5-C3 ACD, CA, USA Cat# 826131-C3

MycoAlert Mycoplasma Detection Lonza, ME, USA Cat# LT07-701

Kit

Enzymes, Culture medium and Chemicals

Collagenase/dispase Roche, Germany Cat# 11097113001

Collagenase II Sigma, Israel Cat# C6885

Collagenase IV Sigma, Israel Cat# C5138

45 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

RQ1 RNase Free DNase Promega, WI, USA Cat# M610A

Trypsin-EDTA (0.25%), phenol Thermo Fisher Scientific, NY, Cat# 25200114

red USA

BSA Sigma, Australia Cat# B2064

DPBS Thermo Fisher Scientific, NY, Cat# 14190144

USA

Red blood cell lysis buffer TBD, China Cat# NH4CL2009

HBSS Thermo Fisher Scientific, NY, Cat# 14025092

USA

Trypan Blue solution Sigma, UK Cat# T8154

10% neutral formalin buffer Slarbio, China Cat# G2161

EDTA (0.5M) Thermo Fisher Scientific, CA, Cat# 15575020

USA

ProLong™ Gold antifade reagent Thermo Fisher Scientific, OR, Cat# P10144

USA

Fibroblast Medium (FM) ScienCell, CA, USA Cat# 2301

Mouse Anti- Fibronectin SANTA CRUZ, TX, USA Cat# sc-8422

monoclonal antibody（EP5）

M-MLV Promega, WI, USA Cat# M1701

Poly(I:C) low Molecular Weight InvivoGen, CA, USA Cat# tlrl-picw

(LMW)

Poly(I:C) high Molecular Weight InvivoGen, CA, USA Cat# tlrl-pic

46 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

(HMW)

R848 MCE, NJ, USA Cat#HY-13740/CS-1

706

Lipofectamine™ 2000 reagent Thermo Fisher Scientific, CA, Cat# 11668019 USA

TB GreeenTM Premix Ex TaqTM TaKaRa, China Cat# RR420A

Opti-MEM™ Reduced Serum Thermo Fisher Scientific, Cat# 31985088

Medium NY, USA

Roswell Park Memorial Institute Thermo Fisher Scientific, NY, Cat# 21870-076

(RPMI) 1640 medium USA

Fetal bovine serum Hyclone, UT, USA Cat# SH30396.03

L-Glutamine Thermo Fisher Scientific, Cat# 25030081

NY, USA

Penicillin-Streptomycin Thermo Fisher Scientific, Cat# 15140122

CA, USA

Alexa Fluor® 488 - Conjugated ZSGB-BIO, China Cat# ZF-0512

Goat anti-Mouse IgG（H+L）

ISD Naked InvivoGen, CA, USA Cat# tlrl-isdn

Software and Algorithms

Matplotlib (Python package) NA https://pypi.org/proje

version 3.0.2 ct/matplotlib/

Python Python Software https://www.python.

org/

Scanpy (Python package) F. Alexander Wolf et al., https://pypi.org/proje

version1.3.7 2018 ct/scanpy/

Scikit-learn (Python package) David Cournapeau et al., https://pypi.org/proje

version0.20.2 2007 ct/scikit-learn/

Seaborn (Python package) NA https://pypi.org/proje

version0.9.0 ct/seaborn/

1023

1024 Primers for qRT-PCR

Species Target gene Primer sequence

Rhinolophus F CTGCAAACTGTGTGCGTCTC RIG-I sinicus R CCTGAAAAACTTCTGCGGCT

F CCTCTGAAAGCAATGCAGAAACT MDA5 R GACTTGCCTGATCTGTGGCT

F GACGGGAGCCAGTTTGAGAA IFN-α R TAAGAGAGCCACTTGTGCCG

F CACGAAACGGACCCTGACTC IFN-γ R AGTGGCTCAGAATGCAGACA

F CACGAAACGGACCCTGACTC IFN-ω R AGTGGCTCAGAATGCAGACA

F TCGTCTGGAGACAGCCTTGGAGG IFNβ1 R TGGCTTTCAAGTGCCGCCTGAT

GAPDH F TTGTCAGCAATGCGTCCTGT

48 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

R AGTGATGGCATGGACTGTGG

F AGAAGCTGAGGAACATGCCC IL-1β R GCAGCTGACGGGTTCTTCTT

F GGAAGAGTTCCCAGCTGACC TNF-α R CTTGAGCTGTCCCTCGGTTT

F AACTCCCTCTCCACAAGCAC IL-6 R GGGGTAGGGAAAGCAGTAGC

F AGCTCACAGGTGACGAATGG TLR3 R GAAGACTTGGAACCGAGGCA

F CCAAGGTGCTTTCCAGTTGC TLR7 R ACCAGACAAACCACACAGCA

F AACCTTTCCCAAGTGCCACA TLR8 R TGACAATTGAAGCGCCTCCT

F TTGAGGTGACCGCCTTCTAC IRF3 R GTCTGGCAGTGTTACTGGCT

F GAGCTTGGTCTTGACCTCCC IRF7 R AAGCAGCGCTTCTACACCAA

Homo sapiens

F AGAGCACTTGTGGACGCTT RIG-I R TGTTTTGCCACGTCCAGTCA

F TGCGCTTTCCCAGTGGATTA MDA5 R TTTGTTCATTCTGTGTCATGGGT

IFN-α F GGGAGGTTGTCAGAGCAGAAA

49 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

R GGTGAGCTGGCATACGAATC

F CCAACGCAAAGCAATACATGA IFN-γ2 R TTTTCGCTTCCCTGTTTTAGCT

F GCCCATGTCATGTCTGTCCT IFN-ω R AAGCAGGTCTCCAGGTGTTG

F TAGCACTGGCTGGAATGAG IFNβ R GTTTCGGAGGTAACCTGTAAG

F CGGAGTCAACGGATTTGGTCGTA GAPDH R AGCCTTCTCCATGGTGGTGAAGAC

F ACAGATGAAGTGCTCCTTCCA IL-1β R GTCGGAGATTCGTAGCTGGAT

F CCCAGGGACCTCTCTCTAATC TNF-α R ATGGGCTACAGGCTTGTCACT

F GCCCTGAGAAAGGAGACAT IL-6 R CTGTTCTGGAGGTACTCTAGGTAT

F AGCCTTCAACGACTGATGCT TLR33 R TTTCCAGAGCCGTGCTAAGT

F AATGTCACAGCCGTCCCTAC TLR73 R TTATTTTTACACGGCGCACA

F TCCTTCAGTCGTCAATGCTG TLR83 R CGTTTGGGGAACTTCCTGTA

F GAGGTGACAGCCTTCTACCG IRF33 R TGCCTCACGTAGCTCATCAC

F TGGTCCTGGTGAAGCTGGAA IRF74 R GATGTCGTCATAGAGGCTGTTGG

1025

1026 References

1027 1 Izaguirre, A. et al. Comparative analysis of IRF and IFN-alpha expression in 1028 human plasmacytoid and monocyte-derived dendritic cells. J Leukoc Biol 74, 1029 1125-1138, doi:10.1189/jlb.0603255 (2003). 1030 2 Kanuri, G. et al. Expression of toll-like receptors 1-5 but not TLR 6-10 is elevated 1031 in livers of patients with non-alcoholic fatty liver disease. Liver Int 35, 562-568, 1032 doi:10.1111/liv.12442 (2015). 1033 3 Li, J. et al. Molecular characterization of RIG-I, STAT-1 and IFN-beta in the 1034 horseshoe bat. Gene 561, 115-123, doi:10.1016/j.gene.2015.02.013 (2015). 1035 4 Moriconi, F. et al. The anti-TNF-alpha antibody infliximab indirectly regulates 1036 PECAM-1 gene expression in two models of in vitro blood cell activation. Lab 1037 Invest 92, 166-177, doi:10.1038/labinvest.2011.160 (2012). 1038

Figure 1. Overview of Chinese horseshoe bat cell atlas. a, Work flow of single cell sequencing.bioRxiv preprint Cells doi: https://doi.org/10.1101/2020.06.30.175778 from two male bat ; this organs version posted were June 30, processed 2020. The copyright for holder transcriptomic for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. amplification, sequencing and data analyzing. b, The expression level of viral receptor genes across organs based on bulk-seq data between bat, human and mouse. The size of circle represents the gene expression level and the colors showed the species. c, Axis on the triangular representation of the distributions of viral receptor genes across the organs in bat, human and mouse. The size of the signals represents the mean gene expression showed as ln (expression + 1). d, UMAP plots of all cells, colored by organ, overlaid with the predominant cell type composing each cluster, n = 82,924 individual cells. e, The number of annotated cell types in each organ.

a Respiratory system Lung Trachea Liver Bulk sequencing Intestine 12 organs Digestive system Tongue Chinese horseshoe bats Pancreas Urinary system Kidney Bladder Cell atlas Spleen Immune system Thymus 19 organs Bone marrow Brow n adipose Single cell sequencing tissues Adipose tissues White adipose 82,924 tissue Individual cells Heart Circulatory system Whole blood Nervous system Brain Muscular system Muscle Innate immune response Integumentary system Wing membrane Primary fibroblast cells Reproductive system Testis b d Mesenchymal cell ACE2 SARS-CoV(-2) and HCoV-NL63 Species Endothelial TMPRSS2 Human Epithelial cell cell SARS-CoV(-2) Bat DPP4 Mouse MERS-CoV Muscle cell EFNB2 ln(exp + 1) HeV and NiV 8.5 NPC1 6.8

EBOV and MARV UMAP 2 5.1 DC NCAM1 3.4 RABV 1.7 ANPEP 0.0 HCoV-229E CXADR B cell Adv and CAV T cell Monocyte Intestine Liver Tongue Lung Kidney Heart Brain Spleen Wing Muscle Brown Adipose White Adipose (Skin) Tissue Tissue Macrophage UMAP 1 c e Bat Brain TMPRSS2 Bladder n = 6037 Brown Adipose Tissue NPC1 CXADR in Muscle Heart NCAM1 Bone Marrow n = 5798 EFNB2 Intestine Brain n = 897 DPP4 20% CXADR in Heart 80% Brown Adipose Tissue n = 8500 Kidney CXADR Heart Liver ACE2 in Muscle ANPEP n = 1019 ACE2 Intestine Lung NPC1 in Skin n = 1777 9.0 Kidney n = 3425 Muscle ANPEP in Muscle 40% TMPRSS2 in Skin 60% 7.2 Liver n = 8678 Skin ACE2 in Tongue Lung n = 8656 Spleen 5.4 Muscle n = 2032 Tongue 3.6 Pancreas n = 4228 White Adipose Tissue 1.8 ACE2 in Skin 60% 40% Skin (wing) n = 8748 TMPRSS2 in Heart Spleen n = 6491 Cell types ACE2 in Spleen Testis n = 1843 ACE2 in Brain ACE2 in Thymus n = 6679 B cell White Adipose Tissue Tongue n = 2068 Endothelial cell 80% TMPRSS2 in Brown Adipose Tissue 20% Epithelial cell ACE2 in Heart Trachea n = 2701 Mesenchymal cell White Adipose Tissue n = 2127 Muscle cell TMPRSS2 in Neuron White Adipose Tissue TMPRSS2 in Liver Whole Blood n = 1220 CXADR in Brown Adipose Tissue NCAM1 in Other immune cell ANPEP in Liver White Adipose Tissue Stem cell 0 4000 8000 TMPRSS2 in Muscle NCAM1 in Spleen NCAM1 in Heart T cell Colors for organs Number of cells othertype 20% 40% 60% 80% NCAM1 in Liver (panel c and d) Mouse Human Figure 2. Differential expressions of bat lung cells compared to human and mouse, and the distribution of viral receptor genes across cell types. a, UMAP visualization and marker-based annotationbioRxiv of preprint lung doi: cells. https://doi.org/10.1101/2020.06.30.175778 Cells are colored by cell-type.; this version posted b, ComparisonsJune 30, 2020. The copyright of the holder differential for this preprint genes (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. expressed in endothelial cells, epithelia cells, mesenchymal cells, and immune cells in bat compared to that of human and mouse. Differential expressed genes with p-adjust<=0.05 were analyzed. Results are visualized by heatmaps of normalized gene expressionand histograms of fold change between cell types. c, Violin plots of viral receptor genes expression in top 5 cell types. a b Epithelial cell Endothelial cell

Mouse Mouse Myofibroblast

Natural killer Mesothelial cell Bat Bat T cell Alveolar fibroblast Ciliated cell AT2 cell T cell Human Human Adventitial

FN1 ADA EMB LUM SLPI CPM SLPI HHIP MMD MMD KRT7 SOX4 fibroblast SOX4 EDN1 AQP1 EMP1 CDH5 AGR2 FMO1 CDO1 BNIP3 PHYH Non-classical ITM2C IL18R1 TRPV2 Untyped HRCT1 CLDN4 CLDN1 STMN2 HRCT1 PSMA6 NEDD4 PI4K2BMMP15ACOT7 BPIFB1 POSTN EPCAM SUMO2 HMOX1 HILPDA ZBTB16 ZBTB16 LRRC58 HS3ST1 COL1A2COL3A1 COL1A1COL6A3 AGPAT2 PLCXD1 LYSMD2 RNASE4 PECAM1 SPOCK2 PITPNC1 SLC34A2 GRAMD2 GPIHBP1AFAP1L1 SLC25A4 SLC34A2 SLCO2A1 SCGB3A1

PPP1R16B PPP1R14C Capillary type 1 cell AT1 cell monocyte

UMAP2 ATP8A2 BPIFB1 KCNMB2 SLPI ATP6V0C SLPI SPOCK2 POSTN HSH2D SCGB3A1 VIPR1 EMP1 Classical SAT2 EMP1 MX1 COL1A2 AGPAT2 CLDN1 FAM57A COL1A1 monocyte ENO1 OAT F8 COL3A1 PLCXD1 MDK PERP COL6A3 RAB17 FOLR1 HRCT1 LUM Neutrophil TRPV2 AQP1 TIMP1 SOX4 Lymphatic cell GRAMD2 SOX4 HOPX NNMT IL1RN STEAP4 RGS5 TMBIM1 IL1B DAZAP2 ADA FN1 HOPX SUMO2 RNASE4 AQP1 Interstitial CDO1 CLDN4 ZBTB16 SUMO2 + C1QA EDN1 HSPB8 DAZAP2 macrophage ALOX5AP ZBTB16 COL1A2 BNIP3 KCTD12 CAV1 AGR2 ADI1 COL6A1 PMP22 MPZL2 GSTO1 MMP2 Capillary type 2 cell Macrophage DPP7 CFH PPA1 LTBP2 FABP3 LSM3 AGER COL6A2 Alveolar macrophage SLC34A2 TRPV2 CBFA2T3 NDUFA7 IRX1 AGER MXRA7 MPV17L2 MED28 GABARAP IMPDH1 RALBP1 B cell GATAD1 HMOX1 GPIHBP1 U2AF1 DYNLRB2 APOE TAPBP EIF3L GRB14 IFI30 DAZAP2 HOPX UMAP1 PPP1R14C RENBP MED28 PSMB10 LIMD1 NADK ANKRD33B HRCT1 c GCSH PLLP PRR7 DAZAP2 CPM HSH2D FMO1 ADA ME1 POLR2F PPP1R16B TOMM5 ACOT7 BSCL2 AQP1 PSMA6 EMB RPP21 ITM2C RNASEK WDR89 EIF4A1 PLVAP GABARAP ITM2C GRAMD2 SUMO2 RGS6 SUMO2 PSMA6 COMT GPS2 OAT NPW STMN2 RNASE4 Intestine enterocyte EGFL6 PLCXD1 TMCC2 CRIP1 TMED3 CDO1 RASGEF1A KCNMB2 IL18R1 CRIP1 CTSL ACER2 Brown Adipose Tissue pericyte -10 0 10 -10 0 10 -10 0 10 -10 0 10 MH BH BH HH MH BH BH HH LogFC LogFC Heart myocardial cell Mesenchymal cell B cell Pancreas smooth muscle cell

Mouse Mouse Intestine tuft cell

Lung AT1 cell Kidney collecting duct Bat Bat epithelial intercalated cell

Kidney distal tubule epithelial cell Human Human Kidney collecting duct

epithelial principal cell FN1 CD2 IL1B GLA VIM DCN SLPI MYC LUM KLF9 BIN1 SLPI MMD CTSL THY1 ETS1 UCP2 PRG4 RGL2 CD27 DDIT4 CDO1 SQLE PTGISITM2C MYOC HOPX FMOD AGER GNG7 KRT18 HOPX ITM2C TRPV2 SFRP2 SFRP4 PRELP MFAP5 ABCA6 CD79A RAMP1 XRCC6 SUMO2 PRKCB HVCN1 WDR89 WFDC2 FBXO32 STEAP1 PTP4A3 FKBP11 CLEC3B AVPR1A SLC4A7 LRRC58 SLAMF7 SPOCK2 SLC25A4 FAM107A PCOLCE2 UNC93B1

TNFRSF17 Testis epithelial cell B4GALNT1

MYOC SLPI SPOCK2 ITM2C Thymus epithelial cell DAPL1 STEAP1 GPR85 CD27 ENO1 NNMT SFTA2 SLPI AVPR1A APOD AGER APOC1 MX1 EMP1 HNRNPA1 SOX4 HOPX FMOD C1QA SPAG4 Pancreas epithelial cell C1QA SFRP4 IL1RN WARS DDIT4 CCDC80 IL1B TAPBP IL1B SUMO2 HOPX DAZAP2 FAM107A MDK DERL3 LSM3 RASSF2 TMBIM1 CDO1 SUMO2 Intestine goblet cell TRPV2 GPNMB CCT6A FKBP11 ZBTB16 COL3A1 SQLE MUC1 RAMP1 PTGIS S100A4 NR4A2 TM4SF1 HAS2 ENO1 CD55 SFTPD CD55 CD63 FN1 Lung mesothelial cell C7 COL1A2 ISG20 DNAJB1 CD36 COL1A1 GYPC PDLIM1 OMD LSM3 PTRF AQP1 LOX AEBP1 WFDC2 SAR1A SOCS2 APOE PTP4A3 ATXN7L3B Whole Blood T cell COMT TOMM5 ETS1 RNASEK WISP2 MRPS24 KLF13 CCND3 MED28 GLRX2 BIN1 PSMB10 CTDSP2 U2AF1 ARHGDIA EIF3L AGPAT4 EIF3L COMT GRAP Spleen endothelial cell COL3A1 COL13A1 CD2 SLC4A7 CLEC3B CLDN5 LIMD1 EBF1 EMP1 DPEP1 FAM111A MRPS24 TMED3 ANKRD11 RP9 ARID4B PRELP RNASEK NCF4 CRIP1 Heart endothelial cell NDRG2 UCP2 CD55 EIF4A1 RCN2 DAPL1 WDR89 TRAPPC5 RCN1 EIF4A1 DAZAP2 U2AF1 PTGIS AVPR1A TAPBP GABARAP SUMO2 ISM1 SUMO2 DDX39B Muscle endothelial cell CTSL PSMA6 NEURL3 GPR85 OAT ANGPTL4 GGA2 SMC6 PCOLCE2 CRIP1 TSPAN32 CDO1 ITM2C RNASE4 B4GALNT1 PSMA6 Brain oligodendrocyte -10 0 10 -10 0 10 MH BH BH HH -10 MH 0 BH 10 -10 BH 0 HH 10 Lung AT2 cell LogFC LogFC

T cell Macrophage\Monocyte\Mast cell Trachea epithelial cell

Mouse Mouse Brain oligodendrocyte precursor cell

Brain astrocyte Bat Bat Brain neuron

Bladder stromal cell Human Human

Tongue taste cell

LAT FN1 EMB IFNG GSR GDA THY1 CD36 RGL2 CD3E CD3D SWI5 AGER CDO1 NCF2 CD46 KLF13 IL1RN ITM2A C1QA AQP3 MSR1 AGER GNG2 CDO1 KYNU S1PR4 TNNT2 FABP4 KLF13 HOPX DUSP4 INHBA NPDC1GNG11APOC1 PLAC8 TNNT2 WDR89 WFDC2 GNGT2 MAPK3 CHI3L1 APOC1 RNF187 TMBIM1MARCO WDR89 LRRC58 PHLDA1 LRRC58 TUBA4A PLXDC2 RNASE4 FAM189B TNFRSF4 SCGB3A1 ATP6V0C PLEKHO1

B4GALNT1 Intestine cell cycle associated cell B4GALNT1

CHIT1 MARCO Intestine enteroendocrine cell TNNT2 MARCO RETN CTSL IL1RN APOC1 TESC APOC1 SPOCK2 DAZAP2 ATP6V0C KYNU AGER TMBIM1 MAPK13 TMBIM1 MX1 ICOS HRCT1 ITM2A C2 FN1 Intestine stromal cell ENO1 GZMM TNNT2 OLR1 C1QA DUSP4 AGPAT2 GPNMB ZBTB16 SUMO2 S100A8 KCTD12 Kidney proximal straight NPDC1 PHLDA1 HRCT1 DAZAP2 HOPX IFNG IL1A SUMO2 HNRNPA1 SEPT9 CHI3L1 AQP3 tubule epithelial cell ANXA1 ARHGDIA ENO1 INHBA SFTPD FABP4 EPHX2 CD46 CD63 CREM HOPX FABP4 Intestine marginal zone B cell WFDC2 FN1 AGER WARS SAP18 SCGB3A1 S100A9 TREM1 SCPEP1 DNAJB1 MS4A7 ARHGDIA S100A4 TAGLN2 BASP1 GCHFR IL1B TANK IL1B NUPR1 Bladder urothelial cell LRRC58 RAMP2 GM2A TRAPPC5 RNF187 GPS2 NONO IFI30 KCNN4 ZBTB16 GNGT2 CHI3L1 NONO PHGDH RASSF4 GNG10 SEPT9 ZGPAT TAPBP EPHX2 Pancreas ductal cell S1PR4 MRPS24 SEPT9 TOMM5 FAM189B GABARAP PLAC8 ITGA4 LAT HRCT1 CSF2RB PSMA6 ARHGDIA PSMA6 COMT LRCH4 SMPDL3A RNASE4 ARHGDIA ZBP1 Kidney mesangial cell RP9 CRIP1 KCTD12 EIF4A1 TAPBP TNNT2 TMED3 IRF9 TSPAN32 RNASEK FAM111A GABARAP ITM2C POLR2F DAZAP2 GPS2 THY1 CHI3L1 PRKCD CDO1 Skin keratinocyte stem cell DAZAP2 PAQR6 SUMO2 TNNT2 SUMO2 TRAPPC5 ATP6V0D2 CRIP1 EMB LIME1 ITM2C HRCT1 4 B4GALNT1 B4GALNT1 RNASE4 CDO1 WDR89 RBP2 Trachea neuroendocrine cell 2 WDR89 DAPL1 0 -10 0 10 -10 0 10 -10 0 10 -10 0 10 ACE2 TMPRSS2 DPP4 EFNB2 NPC1 NCAM1 ANPEP CXADR MH BH BH HH MH BH BH HH LogFC LogFC Figure 3. Analysis of bat T and B cells. a, UMAP visualization of all T cells from Chinese horseshoe bats, showing the formation of 13 main clusters shown in different colors. The functional description of each cluster is determined by the gene expression characteristics of each cluster. n = 9,663 individual cells. b, Violin plots bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint showing the enriched(which was transcripts not certified of by differentpeer review) T is cellthe author/funder. clusters. c, All Violin rights reserved. plots Noshowing reuse allowed the enriched without permission. transcripts of TRM- high high GZMA , TRM-ZNF683 , and IEL. d, UMAP visualization of NKT-like-1, NKT-like-2, and NKT-like-3 cells. Colors indicate different organs, and shapes indicate cell types. e, UMAP plots showing expression of selected long- lived effector genes and immediate early genes (IEGs) in this dataset. f, Violin plots showing the enriched transcripts of NKT-like-1, NKT-like-2, and NKT-like-3 cells. g, Tissue preference of each NKT-like cell cluster estimated by proportion. h, UMAP visualization of B cells from Chinese horseshoe bats, showing the formation of 10 main clusters shown in different organs. The functional description of each cluster is determined by the differential expressed genes. i, Dot plot visualization of selected marker gene for each cell type. The size of the dot encodes the percentage of cells within a cell type in which that marker gene was detected, and the color encodes the average expression level. j, Distribution of B cell types in different organs.

a b ln(exp + 1) c 0 4 8 LEF1 TN high C8_TRM-GZMA CCR7 C6_TEM/TH1-like

high TCF7 high 6 C9_TRM-ZNF683 IL2RA TREG 4 CCR8 -GZMA 2 C10_TEMRA

CTLA4 RM

T 0 C13_Proliferating T GPR183 T /T 1-like EM H GZMA GNLY PRF1 APOA4 FABP1 MAPT CXCR3 C1_CD4TN C12_NKT-like GZMK high NKG7 6 IFNG 4

GNLY 2 -ZNF683 UMAP2 ITGAE RM 0 ZNF683 NKT-like T ZNF683 IFNG IRF7 TBX21 APOC1 APOE C11_IEL KLRD1 KLRF1 6 NCR1 TH17 C7_TH17 CD44 4 IEL RORC 2 C5_T IL23R EM 0 C3_TREG-like MKI67 C4_TCM C2_CD8TN ITGAE TIMP1 RGS1 FCER1G CD44 FKBP5 CD9 PI3 RND3 LGALS3 Proliferating 17 IEL NKT CD4 CD8 TREG TCM TEM TEM TH TRM TRM TEMRA + + like T T T like TH1-like GZMA ZNF683 UMAP1 N N d e f g KLRG1 ITGA4 GZMA 10 10 10 Bladder 0 2 4 6 8 8 8 8 Bone Marrow Bladder ITGA4 Bone Marrow Brown Adipose Tissue 6 6 6 KLRG1 Brown Adipose Tissue Intestine UMAP2 UMAP2 UMAP2 Kidney 4 4 4 KLF2 NKT-like-1 Kidney Liver GZMA Liver Lung 2 2 2 Pancreas CRTAM Lung 0 0 0 UMAP1 UMAP1 UMAP1 Spleen PI3 Pancreas NKT-like-2 JUND NR4A1 FOSB UMAP2 Thymus 10 10 10 CMC1 Skin (wing) Trachea Spleen White Adipose Tissue 8 8 8 ITGAE Whole Blood Thymus NKT-like-3 SCGB3A1 6 6 6 NKT-like-1 Tongue MAPT

NKT-like-2 UMAP2 UMAP2 UMAP2 4 4 4 Trachea NKT-like-3 GNLY White Adipose Tissue 2 2 2 BCL2 Whole Blood

UMAP1 0 0 0 UMAP1 UMAP1 UMAP1 NKT-like-1 NKT-like-2 NKT-like-3 0 20 40 60 80 100

h j Bladder C3_Marginal Zone B cell Bone Marrow C2_Germinal center B cell Brown Adipose Tissue Heart Bladder Intestine Bone Marrow Brown Adipose Tissue Kidney Heart Intestine Liver Kidney Liver Lung Lung UMAP2 C5_Plasma cell Muscle Muscle Pancreas Spleen Pancreas Thymus Spleen Tongue C1_Activated B cell Trachea Thymus Naïve/memory B cell White Adipose Tissue Whole Blood Tongue Activated B cell Trachea

cluster Plasma cell White Adipose Tissue Germinal center B cell C4_Naive/memory B cell Whole Blood Marginal Zone B cell UMAP1 0 500 1000 1500 i

Germinal center B cell 3 2 Naive/memory B cell 1 0

Activated B cell 1.0 0.8 0.6 Marginal Zone B cell 0.4 0.2

Plasma cell BCL6 DTX1 CD69 CD86 CD19 XBP1 MZB1 SDC1 KIF11 RGS1 EGR1 CAPG MKI67 STAP1 FABP4 MYBL1 RGS13 ANXA2 LAMP3 MS4A1 DPEP1 TOP2A UBE2C CENPF CDCA3 CDKN3 PTCRA AHNAK PIK3R1 ABLIM1 ARID5B ZBTB38 FKBP11 PHLDA2 KDELR3 DTNBP1 TXNDC5 MARCKS PHACTR1 TNFRSF17 LOC109451464 LOC109458629 LOC109457968 NW_017739275.1:124060-124578 NW_017739384.1:713782-714189 NW_017739179.1:411716-414938 NW_017739410.1:938146-938785 NW_017739451.1:475875-476225 NW_017739063.1:247007-253727 NW_017739179.1:1283472-1285430 NW_017739111.1:2549215-2549625 NW_017739111.1:5559126-5559573 NW_017738957.1:14403809-14405173 vesicular stomatitisvirus(VSV).Errorbarsrepresentstandarddeviation. of infection the after TNFα and IL-6, IFNβ, RIG-I, MDA5, of levels Expressions f, (I:C). poly of inoculations the after IFNβ and IL-6 of levels Expressions e, B848. of transfection the after TNFα IL-6, of d, levels Expressions (I:C). poly of transfection the after IFNβ RIG-I, MDA5, of levels Expressions c, probe. RNA 1 fibronectin with hybridization situ in fluorescence single-molecule by confirmation type Cell b, isolation. fibroblast primary fibroblast. lung primary bat in interferon I type of levels Expression 4. Figure bioRxiv preprint f e d c a

Relative IFNβ expression Relative VSV expression1800000 2200000 RelativeTLR3 expression RelativeTLR7/8 expression Relative MDA5 expression 120000 160000 200000 (which wasnotcertifiedbypeerreview)istheauthor/funder.Allrightsreserved.Noreuseallowedwithoutpermission. 10000 20000 1000 1500 2000 5000 1000 1500 2000 2500 100 150 200 500 200 400 500 10 20 30 40 50 50 10 15 0 0 0 5 0 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 doi: *** HPF BPF *** HPF TLR8 TLR8 BPF HPF TLR7 TLR7 BPF HPF BPF HPF BPF HPF BPF *** https://doi.org/10.1101/2020.06.30.175778 *** *** *** Poly I:C (h) Poly I:C (h) R848 (h) VSV (h) VSV (h) *** *** *** *** *** Bat pneu.Batfibroblast *** *** *** 1000 Relative IL-6 expression1000 1500 2000 Relative MDA5 expression Relative IL-6 expression Relative IL-6 expression Relative RIG-I expression 1000 200 400 600 800 500 100 120 140 200 400 600 800 100 200 300 400 10 20 30 10 15 20 25 60 80 10 15 20 20 40 60 0 0 5 0 5 0 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 *** HPF BPF HPF BPF HPF BPF HPF BPF HPF BPF ; *** this versionpostedJune30,2020. *** *** *** Poly I:C (h) b R848 (h) VSV (h) VSV (h) *** *** *** *** Poly I:C (h) *** FN1 20× *** *** *** ***

Relative TNFα expression Relative RIG-I expression Relative IFNβ expression Relative TNFα expression Relative IFNβ expression1000 1500 2000 150 200 250 300 100 500 10 15 20 10 15 20 60 80 20 40 10 20 30 40 50 10 20 30 40 50 0 5 0 5 0 0 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 01 025 20 15 10 5 0 FN1 63× The copyrightholderforthispreprint HPF BPF HPF BPF HPF BPF HPF BPF HPF BPF *** *** a, Work flow of bat pulmonary bat of flow Work a, *** *** *** Poly I:C (h) R848 (h) VSV (h) VSV (h) *** *** ** *** Poly I:C (h) *** *** *** *** Extended Data Figure 1. Transcriptomic analysis by bulk sequencing and the comparisons to single cell sequencing. a, Expression level of selected viral receptor genes in organs based on bulk-seq data of bat and human. Adv: Adenovirus; RSV: Respiratory syncytial virus; MV: measles virus; CAV: Coxsackie virus; CAV-A9: bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint Coxsackie virus(which A9; was not CAV-A16: certified by peer Coxsackie review) is the virus author/funder. A16; All CAV-A13/18/21: rights reserved. No reuse Coxsackie allowed without virus permission. A13/18/21; HRV: Rhinovirus; EchoV: Echovirus; DENV: Dengue virus; EV-B: Enterovirus B; HSV-1:Herpes simplex virus; HCMV: human cytomegalovirus; VZV: Varicella zoster virus; VSV: Vesicular stomatitis virus. b, Histogram of the number of detected genes (left) and UMIs (right) per cell for each organ. c, Dot plot visualization of differentially expressed genes across clustered cells. d, The comparison of differential transcriptional genes between bulk-seq and single cell (sc)-seq data in each organ. a d

ATP1B2 TUBB4A Adv RSV MV MV KIF1A NEFL MBP N CDR1 S CPLX2 GABBR1 E MAP1A NCDN D L ALDOC N C CAMK2A SNAP25 S A TMEM59L C T KIF5C UCP1 G M TNNT2 L I TNNI3 TNNC1 2 F MYL4 MYL2 N VIL1 1 DNPEP MYO1A 4 SEC14L2 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 LAP3 FABP2 TFF3 Bat Human Bat Human Bat Human Bat Human TFF2 ACE2 GPA33 RBP2 KRT20 FABP1 CAV CAV-A9 CAV-A16 CAV-A16 MGAM FCGBP LGALS4 PLS1 S S ZG16 I CLDN3 SLC15A1 C C E CCL25 AOC1 T APOA4 D A L MUC2 CDHR5 G PYDC1 5 R P SI CDH17 A HNF4G 5 B L TMEM54 REG4 V PLAC8 GUCA2A 2 G PLCB3 SPINK1 KCNJ16 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 KLK1 TMEM27 Bat Human Bat Human Bat Human Bat Human S100G SLC5A12 TSPAN1 PDZK1IP1 UMOD HRV CDH16 CAV-A13/18/21 HRV EchoV/EDNV/Norovirus CA12 SLC34A1 DNASE1 MIOX AQP2 LRP2 V I H MSRA L SDSL LRG1 C C S SERPINA1 D SERPINA3 KNG1 A A P AMBP APOC2 L APOC4 M M G APOC1 HPX R C3 1 1 2 AGXT APOA2 APOC3 APOA1 CFB 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 TTC36 ANG ALB Bat Human Bat Human Bat Human Bat Human GC SERPINC1 ITIH4 CPS1 ARG1 Orthoreovirus EV-B HSV-1 HSV-1 ANGPTL3 APOH TDO2 N FGG FGB HPD F E AHCY F FETUB M AHSG C C SPP2 1 CALCRL Y SFTPC G T SFTPB AGER 1 H ANXA3 R I RTKN2 SCGB3A2 R 9 CUNH8orf22 KRT10 T N TNS4 CUNH10orf99 KRT1 1 GPNMB 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 AIF1 CD53 SPIC Bat Human Bat Human Bat Human Bat Human CSF1R ADA ALDH3A1 MUC5B PIP BPIFB1 HSV-1 HCMV VZV VSV BPIFA2 FAM25A LACRT P Brain LEP P I Heart D Intestine Liver Lung Brain I I G Kidney Heart Kidney Spleen G Muscle Liver Tongue L D F Intestine Tissue Lung

F Skin (wing) R E 2 Muscle R Skin (wing) A R Spleen A White Adipose Tissue White Adipose Tissue

7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 Brown Adipose Tissue Bat Human Bat Human Bat Human Bat Human Bulk-seq ScRNA-seq b c 0 4 8 0 2 4 Bladder n =6037 Bone Marrow n =5798 Percent expressed Relative expression n =897 Brain 0.20 0.40 0.60 0.80 1.00 Brown Adipose Tissue n =8500 0 1 2 3 Organs Bladder n =1019 Bone Marrow Heart TNFRSF13B Brain VPREB3 Brown Adipose Tissue Intestine n =1777 CD79B Heart KDR Intestine Kidney n =3425 F8 Kidney FLT1 Liver Lung Liver n =8678 DSP Muscle TACSTD2 Pancreas n =8656 KIF21A Skin (Wing) Lung OGN Spleen FMO2 Testis Muscle n =2032 ASPN Thymus PGM5 Tongue n =4228 POSTN Trachea Pancreas White Adipose Tissue GUCY1B3 Whole Blood n =8748 CHN1 Skin (wing) PCP4 Cell types n =6491 MAP1A B cell Spleen CUNH1orf162 Endothelial cell NFAM1 Epithelial cell n =1843 SPI1 Mesenchymal cell Testis Muscle cell CD247 Neuron Thymus n =6679 CD3D Other immune cell CD3E Stem cell T cell Tongue n =2068 othertype Trachea n =2701 White Adipose Tissue n =2127 Whole Blood n =1220

0 1000 2000 3000 4000 5000 0 2000 6000 10000 14000 18000 Genes per cell UMI per cell Extended Data Figure 2. Analysis of the cell types and receptor genes distribution patterns in single cell level. a, UMAP plots of expression for genes specifically expressed in particular cell types (SFTPC in AT2 and CLDN5 in endothelial cells). Gene expression levels are indicated by shades of red. b, Single-molecule fluorescence in situ hybridization of SFTPC (Opal 520) and CLDN5 (Opal 690) on lung single cells droplet slices. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint c, Dot plot visualization(which ofwas selected not certified marker by genes peer forreview) each iscell the type. author/funder. The size of All the rights dot encodesreserved. the No percentage reuse allowed of cells without within permission. a cell type in which that marker was detected, and the color encodes the average expression level. d, UMAP visualization and marker-based annotation of trachea cells. Cells are colored by cell-type. e, UMAP visualization and marker-based annotation of kidney cells. Cells are colored by cell-type. f, UMAP visualization and marker-based annotation of intestine cells. Cells are colored by cell-type. g, Comparisons of the expression patterns of the respiratory virus receptor genes, ACE2, DPP4, ANPEP, CXADR and the TMPRSS2 in endothelial cells, epithelia cells, and mesenchymal cells in single cell levels in bat compared to that of human and mouse. Only epithelial cells in intestine and kidney were selected for the comparisons according to the available data. SARS-CoV, Severe acute respiratory syncytial virus; HCoV, Human coronavirus; Adv: Adenovirus; CAV: Coxsackie virus .

b a SFTPC CLDN5 SFTPC CLDN5 3500 160 3000 140 2500 120 100 2000 80 1500 UMAP2 UMAP2 60 1000 40 500 20 0 UMAP1 UMAP1

Percent expressed Relative expression 0.20 0.40 0.80 1.00 c 0.60 0 2 4 6

Adventitial fibroblast AT1 cell AT2 cell Alveolar fibroblast Alveolar macrophage B cell Capillary type 1 cell Capillary type 2 cell Ciliated cell Classical monocyte Interstitial macrophage Lymphatic cell Macrophage Mesothelial cell Myofibroblast Natural killer T cell Neutrophil Non-classical monocyte T cell Untyped LTF PI16 KDR LUM LIPG CD14 CD28 TPM2 LVRN CD3E NCR1 CD3D C1QA NCR3 NKG7 C1QC MSLN CHIT1 LYVE1 CD163 CD177 TLCD2 CD79A FADS3 CD79B C4BPA PDE3A BANK1 LAMP3 RTKN2 ELANE RSPH1 PTPRB ABCG1 PDLIM3 MMRN1 CLDN15 OLFML3 CX3CR1 SPACA9 SCARA5 FCGR3A GPRC5A PECAM1 TYROBP PLA2G1B ALOX5AP SCGB3A1 SERPINA3 ln(exp+ 1) d e Trachea Kidney f Intestine Non-classical monocyte KPSTE cell T cell Classical monocyte Goblet cell Macrophage Stromal cell B cell Endothelial cell associatedCell cycle cell Endothelial cell Natural killer T cell Dendritic cell KCDE cell (intercalated cell) KDTE cell Clara cell KCDE cell MarginalB cell zone UMAP2 UMAP2 Ciliated Mesangial cell (principal cell) UMAP2 Brush cell columnar cell Epithelial cell T cell Myofibroblast Macrophage cell Mesenchymal cell Enteroendocrine Macrophage B cell Enterocyte Neuroendocrine cell Tuft cell UMAP1 UMAP1 UMAP1 g Lung Trachea Intestine Kidney

ACE2 (- ) SARS-CoV 2 12.0 HCoV-NL63 3.0 TMPRSS2 2.2 SARS-CoV (-2) 1.5 0.8 DPP4 0.0 HCoV-229E ln (exp+ 1）

ANPEP Epithelial cell HCoV-229E Endothelial cell Mesenchymal cell

CXADR Mouse Adv and CAV Bat Human Extended Data Figure 3. The known human viral receptors genes expressed in bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint bat across(which was the not certifiedcell types. by peer review) Dot isplots the author/funder. of expression All rights reserved.for viral No receptorreuse allowed genes without permission.in featured

cell types. The size of the dot encodes the percentage of cells within a cell type in

which that marker was detected, and the color encodes the average expression level.

Intestine enterocyte Brown Adipose Tissue pericyte Heart myocardial cell Pancreas smooth muscle cell Intestine tuft cell Bladder mesenchymal stromal cell Muscle cell 4 Thymus smooth muscle cell Intestine stromal cell Bladder vascular smooth muscle cell Lung AT1 cell Kidney collecting duct epithelial intercalated cell Kidney distal tubule epithelial cell Kidney collecting duct epithelial cell (principal cell) Testis epithelial cell 3 Kidney mesangial cell Thymus epithelial cell Pancreas epithelial cell Intestine goblet cell Lung mesothelial cell Whole Blood T cell Intestine cell cycle associated cell Spleen endothelial cell 2 Heart endothelial cell Muscle endothelial cell Brain oligodendrocyte Lung AT2 cell Trachea epithelial cell Brain oligodendrocyte precursor cell Brain astrocyte 1 Brain neuron Bladder stromal cell Tongue taste cell Intestine enteroendocrine cell Kidney proximal straight tubule epithelial cell Intestine marginal zone B cell Intestine endothelial cell Intestine T cell 0 Intestine macrophage White Adipose Tissue mesenchymal stem cell Brain pericyte Skin epidermal basal cell Testis sertoli cell Pancreas alpha cell Brown Adipose Tissue mesenchymal stem cell Testis leydig cell Trachea mesenchymal cell Tongue stromal cell Bladder urothelial cell Pancreas ductal cell 100% Skin keratinocyte stem cell Trachea neuroendocrine cell Skin epidermal cell Liver duct epithelial cell 80% White Adipose Tissue dendritic cell Lung classical monocyte Bone Marrow hematopoietic stem cell Kidney B cell Spleen proliferating B cell 60% Bone Marrow granulocyte-monocyte progenitor Skin T cell Skin melanocyte Tongue keratinocyte 40% Brain T cell Whole Blood B cell Trachea natural killer T cell Testis myofibroblast Muscle stromal cell 20% Heart T cell Bone Marrow promonocyte Skin langerhans cell Muscle natural killer T cell Muscle T cell Trachea non-classical monocyte Kidney macrophage Whole Blood non-classical monocyte Heart fibroblast Brown Adipose Tissue smooth muscle cell Thymus mesenchymal cell Brain microglial cell Trachea brush cell Bone Marrow multi-lymphoid progenitor Pancreas stellate cell Liver kuffer cell Lung alveolar fibroblast Liver endothelial cell of hepatic sinusoid Pancreas stromal cell Brain endothelial cell Lung adventitial fibroblast Lung untyped Muscle mesenchymal stem cell White Adipose Tissue macrophage Testis endothelial cell Lung ciliated cell Liver hepatocyte Trachea ciliated columnar cell Liver macrophage Lung macrophage Whole Blood classical monocyte Trachea macrophage Brown Adipose Tissue nacrophage Muscle dendritic cell Muscle macrophage Spleen macrophage Testis macrophage Spleen classical monocyte Lung non-classical monocyte Bone Marrow granulocyte Thymus macrophage Bone marrow Monocyte Tongue langerhans cell Bone Marrow macrophage White Adipose Tissue endothelial cell Lung alveolar macrophage Trachea myofibroblast Bladder smooth muscle cell Thymus endothelial cell Pancreas endothelial cell Brown Adipose Tissue endothelial cell Testis peritubular myoid cell Lung myofibroblast Tongue endothelial cell Tongue muscle cell Trachea endothelial cell Bladder endothelial cell Lung capillary type 1 cell Lung lymphatic cell Lung capillary type 2 cell Bladder macrophage Pancreas macrophage Lung interstitial macrophage Liver dendritic cell Testis spermatogonial stem cell Heart macrophage Brown Adipose Tissue brown adipocyte Trachea dendritic cell Bladder dendritic cell Muscle B cell Liver B cell Trachea classical monocyte Liver T cell Pancreas dendritic cell Tongue supporting cell Whole Blood neutrophil Lung T cell Lung neutrophil Brown Adipose Tissue T cell Bladder T cell Thymus CD8+ thymic T cell Kidney T cell Brown Adipose Tissue dendritic cell Bone Marrow T cell Spleen natural killer T cell Bone Marrow naïve T cell Lung natural killer T cell Bone Marrow natural killer T cell Bone Marrow granulocytopoietic cell Spleen T cell Heart B cell

IDE ACE2 DPP4EFNB2NPC1 ICAM1DSG2NCL CD55ITGAV LDLR F11R MYH9 PILRA IGF2R TMPRSS2 NCAM1ANPEPCXADR NECTIN4SLAMF1 SCARB2SELPLGVCAM1 HSPG2 FCGRT NECTIN1 PDGFRA Extended Data Figure 4. Summary of functional properties of various T cell clusters. a, Heatmap of bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint unique signature(which genes was not for certified thirteen by peer T review) cell clusters. is the author/funder. Selective All rightsspecifically reserved. Noexpressed reuse allowed genes without are permission. marked alongside. b, UMAP plots of expression levels of selected genes in different clusters indicated by the coloured oval corresponding to Figure 3a. c, Overview of T cell cluster characteristics. d, The number of activated T cells and naïve T cells in different tissue.

a b

CD4 CD8 TEM TRM TRM NKT Proliferating CCL5 CCR7 CCR8 CD4 10 TREG + + Cluster T T T 1-like GZMA ZNF683 TEMRA T T like CM EM H TH17 IEL like T N N 8 IGLL1 6 RARRES1 AIF1 CTSS 6.0 4 CTSC CAMP 2 PGLYRP1 LCN2 ELANE 4.5 0 LTF IL2RA CD8A CD9 CD44 CTLA4 10 CUNH12ORF75 LXN 8 PMAIP1 3.0 NPDC1 FABP4 6 CD36 CTLA4 4 TSPAN13 1.5 S100P CCR5 2 BST2 ZBTB16 0 CTSW 0.0 C1QA GPR183 GZMK IFNG IL23R 10 IFNG ISG20 8 FASLG GADD45B HPX 6 CXCL8 SCGB3A1 4 SFTPC IL23R SCGB3A2 2 GNLY APOA4 0 FABP1 ANPEP ITGAE KLRD1 LEF1 MKI67 10 AKAP5 ZNF683 8 HPD ALDOB CLEC4G 6 ASS1 KLRG1 4 KLRB1 ACOT7 STAP1 2 S100A2 RND3 0 MYL10 LY6G6C TBX21 TIGIT XCL1 ZNF683 10 LY6D PANK3 8 TIMP1 GZMK LAT2 6 NCR1 PLEK 4 UBE2C CENPF TOP2A 2 PCLAF MKI67 0 c e Cluster Functional prorerties Representative genes C1 CD4T LEF1, SELL, CD4, CCR7 N Bladder C2 CD8TN LEF1, SELL, CD8, CCR7, TCF7,

C3 TREG-like IL2RA(CD25), CCR8, CCR4 Bone Marrow

C4 TCM GPR183, SELL, CCR7 Brain C5 TEM CXCR3, GZMK, CCL5, CTSW, NKG7 T -T 1-like C6 EM H IFNG, CD4, CXCR3, GZMK, CCL5, CTSW, NKG7 Brown Adipose Tissue

C7 TH17 RORC, IL23R, IF7R, IL1R1, KLRB1 high Heart C8 TRMGZMA ITGAE, GZMA, GNLY, TXK, CCL5, PRF1, NKG7 high C9 TRMZNF183 ITGAE, ZNF683, CCL5, GZMA, NKG7, TBX21, NCR1, CD244 Intestine C10 TEMRA NCR1, ZNF683, NKG7, BHLHE40, KLRB1, FCER1G, CCR5, CCL5, CSTW, CXCR3 C11 IEL ITGAE, NCR1, CTSW, TXK, CD244, CD44, CD7, KLRB1, TCF7 Kidney C12 NKT-like subset-1 CCL5, TBX21, KLRB1, KLRD1, KLRF1, KLRG1, NCR1, NCR3, CTSW, GZMK, Liver NKG7, FCER1G, TIMP1, EOMES, EFHD2, TIGIT, SELL Lung subset-2 CD69, KLRB1, KLRD1, KLRF1, KLRG1, NCR1, NCR3, TBX1, NKG7, GZMK, FCER1G, CD8TN TIMP1, EOMES, CTSW, EFHD2, TIGIT, SELL Muscle CD4TN subset-3 FCER1G, KLRB1, KLRD1, KLRF1, NCR1, NCR3, NKG7, MAPT, USP39, Pancreas IEL SCGB3A1, SCGB3A2 high C13 Proliferating T MKI67, CENPF, TOP2A, PCLAF, CDCA3, CCNA2, BIRC5, CDKN3 TRM-GZMA Skin (wing) high TRM-ZNF683 Spleen NKT-like-CD69+ + 1400 Tcell NKT-like-SCGB3A1 Thymus + 1200 Activated T cell NKT-like-TBX21 d Naive T cell Proliferating T 1000 Tongue TCM 800 Trachea TEM 600 T /T 1-like White Adipose Tissue EM H 400 TEMRA T 17 200 Whole Blood H Number of cells TREG-like 0 0 200 400 600 800 1000 1200 1400 1600 1800 Liver Lung Heart Kidney Spleen Muscle Tongue Bladder Thymus Trachea Intestine Pancreas Skin (wing) Whole Blood Bone Marrow

Tissue White Adipose Tissue Brown Adipose Tissue Extended Data Figure 5. Analysis of mononuclear phagocytes. a, UMAP visualization of mononuclear bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint phagocytes from(which Chinese was not certifiedhorseshoe by peer bats, review) showing is the author/funder. the formation All rights reserved.of 13 main No reuse clusters allowed shownwithout permission. in different organs. The functional description of each cluster is determined by the gene expression characteristics of each cluste r. b, Dot plot visualization of each cell type and selected marker gene. The size of the dot encodes the percentage of cells within a cell type in which that marker was detected, and the color encodes the average expression level. c, Tissue preference of mononuclear phagocytes estimated by proportion based on 10x data.d, Gene ontology analysis of macrophage with high expressions of CCL26, CD300, CSF1R, LYVE1 and SPIC.

a c d Whole Blood high C1_ncMo CCL26 M ac C9_GMP White Adipose Tissue C12_pDC Bladder lipid catabolic process C3_cMo Bone Marrow Trachea lipid localization Brown Adipose Tissue regulation of endocytosis Tongue lipid storage 0.0001 C0_CSF3Rhigh Mac Heart positive regulation of lipid metabolic process 0.0002 C6_CCL26high Mac Intestine Thymus lipid transport C7_cDC1 cellular response to lipoprotein particle stimulus Kidney Testis regulation of inflammatory response regulation of leukocyte migration Liver Spleen Lung T cell proliferation Muscle Skin (Wing) 0 5 10 C8_LC Pancreas Pancreas Skin (wing) Muscle Spleen CD300EhighM ac high Lung C10_CD300E Testis

UMAP2 C11_Activated DC neutral lipid metabolic process Mac Thymus Liver triglyceride metabolic process Tongue Kidney small GTPase mediated signal transduction Trachea negative regulation of wound healing 0.0025 Intestine response to inorganic substance C2_KC White Adipose Tissue 4.0 endothelial cell proliferation 0.0050 high Heart Ras protein signal transduction C5_LYVE1 Mac Whole Blood 3.2 negative regulation of blood coagulation Brown Adipose Tissue epithelial cell migration 2.4 regeneration Bone Marrow 1.6 0 5 10 Bladder 0.8 0.0

high LC C4_SPIC Mac KC high cMo Mac Mac Mac Mac GMP Mac

ncMo CFS3R M ac cDC1 pDCs high high high high high leukocyte migration leukocyte chemotaxis NADP metabolic process UMAP1 SPIC Activated DCs Activated CCL26 CSF3R

LYVE1 positive regulation of response to external stimulus CD300E leukocyte cell-cell adhesion 0.0005 regulation of hemopoiesis 0.0010 b regulation of inflammatory response positive regulation of cytokine production GMP T cell proliferation regulation of lymphocyte activation cMo Relative 0 5 10 expression ncMo 6 high C FS 3Rhigh Mac LYVE1 M ac 4 high response to wounding CD300E Mac reactive oxygen species metabolic process 2 protein activation cascade epithelial cell migration 0.00025 KC 0 wound healing complement activation, classical pathway 0.00050 high endothelial cell migration SPIC Mac Persent regulation of vasculature development expression regulation of angiogenesis CCL26high Mac myeloid cell differentiation 1.0 high 0 5 10 LYVE1 Mac 0.8 LC 0.6 SPIChighM ac cDC1 0.4 positive regulation of monocyte chemotaxis small GTPase mediated signal transduction 0.2 myeloid leukocyte activation Activated DC activation of immune response Ras protein signal transduction 0.02 macrophage activation pDC complement activation 0.04 multicellular organismal homeostasis T cell activation protein activation cascade LPO SCD IL7R HPX IRF8 MPO IDO1 FLT3 SPIC SELL TCF4 CD14 CPVL RBP2 DAB2 XCR1 CCR2 CCR7 CTSG AGER CHIT1 ITGA1 0 5 10 LYVE1 CCL26 LPAR3 PRTN3 GPR34 LAMP3 PMP22 SFTPC CSF3R ELANE ADTRP VCAM1 GPM6B EPCAM MARCO CD300E CLEC9A DUSP10 CX3CR1 CLEC4G FCGR3A SLC40A1 TACSTD2 CNTNAP2 MARCKSL1 SERPINA12 Extended Data Figure 6. Analysis of innate immune gene mRNA expression in Chinese horseshoe bat bioRxiv preprint doi: https://doi.org/10.1101/2020.06.30.175778; this version posted June 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. tissues. Tissue mRNA expression levels of RIG-I, MDA5, TLR3, TLR7, TLR8, TLR9, IRF3, IRF7, IFNα,

IFNβ, IFNω and IFNr were determined by qRT-PCR and normalised relative to GAPDH. Error bars represent standard deviation.

0.1000 RIG-I 0.1000 IRF3

0.0750 0.0750

0.0500 0.0500

0.0250 0.0250

0.0000 0.0000

0.0060 MDA5 0.2500 IRF7

0.0045 0.2000 0.0030 0.1500 0.0015 0.0500

0.0005 0.0250

0.0000 0.0000

0.0150 TLR3 0.0025 IFNα 0.0020 0.0100 0.0015

0.0010 0.0050 0.0005

0.0000 0.0000

1.2500 TLR7 0.0200 IFN β 1.0000 0.7500 0.0150 0.4500 0.0100 0.3000

0.1500 0.0050

0.0000 0.0000 Relative expression(2^- Ct) 0.1500 TLR8 0.0500 IFNω 0.1000 0.0400 0.0500 0.0050 0.0300

0.0200 0.0025 0.0100

0.0000 0.0000

0.0450 TLR9 0.3000 IFNγ 0.1500

0.0300 0.0300

0.0150 0.0150

0.0000 0.0000 Liver Liver Lung Lung Brain Brain Heart Heart ong ue ong ue Kidney Kidney Spleen Spleen Muscle Muscle T T Intestine Intestine Skin(wing) Skin(wing) White Adipose Tissue White Adipose Tissue Brown Adipose Tissue Brown Adipose Tissue 2 1 MYD88 CXCR5 NFKB2 NFKB1 TLR10 STING bioRxiv preprint IFNB1 CGAS MAVS MDA5 TNFα TLR9 TLR8 TLR7 TLR6 TLR5 TLR4 TLR3 TLR2 TLR1 RIG-I TRIF epithelial cells,endothelialcellsandstromalcells. Extended Data Figure 7. IRF7 IRF3 IL1β (which wasnotcertifiedbypeerreview)istheauthor/funder.Allrightsreserved.Noreuseallowedwithoutpermission. doi:

AT1 cell https://doi.org/10.1101/2020.06.30.175778

AT2 cell Heatmap of innate immune response genes expression inlung Ciliated cell

Capillary type 1 cell ; this versionpostedJune30,2020. Capillary type 2 cell

Alveolar fibroblast

Adventitial fibroblast The copyrightholderforthispreprint Mesothelial cell

Myofibroblast 0.0 0.8 1.6 2.4 3.2 4.0