Infections with novel human coronavirus 2019 (HCoV-19) 1,2 , named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses (ICTV) 3 , can result in coronavirus disease 2019 (COVID-19), characterized by various clinical outcomes from asymptomatic infections to severe pneumonia and even death 4, 5 . Globally, as of Feb 28 th 2023, over 758 million confirmed cases and over 6.8 million deaths have been reported (covid19.who.int). Human cases with COVID-19 were first reported in late December 2019, in Wuhan, China, as pneumonia of unknown etiology (PUE). A majority of these early cases were found to be linked to the Huanan Seafood Market (HSM) in Wuhan 4, 6 , where various animal meats, exotic seafood and live animals were available for purchase. The HSM has been suspected to be the source of the COVID-19 pandemic 7 . Not all of the early human cases had epidemiological links to the market 6, 8 and alternative hypotheses for the market association, for example entry of virus into the market via humans or the cold-chain, also exist. SARS-CoV-2 has high similarity with a few coronaviruses derived from bats in Asian countries including China, Laos, Japan, Cambodia and Thailand, and some scientists have proposed that bats might be the original source of SARS-CoV-2 1,8-14 . Whether another animal might have acted as an intermediate host to facilitate virus spillover from bats to humans is still unknown 15, 16 . An important finding was the discovery of SARS-CoV-2-related coronaviruses from pangolins, in which the spike proteins contained receptor-binding domains (RBD) showing high similarity to the RBD of SARS-CoV-2 [17] [18] [19] . Pangolins might be involved in the ecology of coronaviruses, but whether they are the intermediate host for SARS-CoV-2 is unknown, given the current data 20 . A recent study documented the animal species in the HSM between May 2017 and November 2019 and noted that no pangolins or bats were present, but some hypothesized sarbecovirus-susceptible animals, such as raccoon dogs were present 21 . Thus far, the origins of SARS-CoV-2 22, 23 and the role of the HSM in the origins and A C C E L E R A T E D A R T I C L E The HSM is located in the Jianghan District in the downtown area of Wuhan, the capital city of Hubei Province, and is approximately 800 m away from Hankou Railway Station, a major railway travel hub. It occupies >50,000 m 2 , with 678 stalls located close to each other in extremely crowded conditions (Fig. 1A ). The market is separated into two zones, the East and West Zones, with seafood and animals mainly sold in the West Zone and livestock meat in the East Zone. Among the 678 stalls of the market, 10 stalls selling domesticated wildlife (1.5%) were identified according to sale records 24 , located in the south-western corner of West Zone (8/10) and the north-western corner of East Zone (2/10), respectively (Fig. 1A ). According to sale records, during late December 2019, animals or animal products were sold in these 10 animal stalls. Animals included snakes, avian species (chickens, ducks, gooses, pheasants and doves), Sika deer, badgers, rabbits, bamboo rats, porcupines, hedgehogs, salamanders, giant salamanders, bay crocodiles and Siamese crocodiles, etc., among which snakes, salamanders and crocodiles were traded as live animals (described in detail in the Report of WHOconvened global study of origins of SARS-CoV-2 24 ). The market was closed in the morning of January 1 st , 2020, shortly after the identification of the PUE. On the same day, in the early morning, the Chinese Center for Disease Control and Prevention (China CDC) dispatched an epidemiological team, together with experts from Hubei Provincial CDC and Wuhan Municipal CDC, to the HSM to collect environmental samples in order to investigate the potential introduction of SARS-CoV-2 to the market (Fig. 1B ). From January 1 st 2020 until March 2 nd 2020, a total of 923 environmental samples from different locations within and around the market and 457 animal samples, including dead animals in refrigerators and freezers and stray animals and their feces, were collected, with some stray animals sampled until March 30 th (Extended Data Tables 1, 2, 3 and Supplementary Table 1 ). After the closure of the market, the outside surface of the rolling shutter doors of the stalls and the corridors were disinfected (with 1% bleach mixed with water) throughout January and February 2020. The goods inside the stalls were completely cleared and disinfected until early March 2020. Out of the 923 environmental samples collected in and around the HSM, 73 were found by the real-time polymerase chain reactions (RT-PCR) to be positive for SARS-CoV-2 with positivity rate of 7.9%. Cycle threshold (CT) values for the RT-PCR ranged from 23.9 to 41.7 (Supplementary Table 2 ). Among the 828 samples inside the HSM, 64 samples (7.7%) were positive. Of the 64 SARS-CoV-2 positive samples collected inside the HSM, 87.5% (56/64) were collected in the West Zone of the market, in particular streets from no. 1 to 8, with 71.4% (40/56) positive samples identified herein (Fig. 1A ). Among the 14 samples from warehouses related to the HSM, five tested positive. This may reflect the nature of SARS-CoV-2 presence in the market during the early phase of the outbreak. Among the 51 samples from sewerage wells (Supplementary Table 1 ) in the surrounding areas outside the HSM, three tested positive (Supplementary Table 2 ). Notably, one sample (Env_0601), a floor surface swab, out of the 30 environmental samples collected from Dongxihu Market in Wuhan on January 22 nd 2020, also tested positive (Supplementary Table 2 , Extended Data Table 4 ). Of the 110 samples collected from sewers or sewerage wells in the market, 24 samples were positive for SARS-CoV-2 nucleic acid. All four sewerage wells in the market tested positive. During the onsite investigation of the overground drainage pathway in the HSM, we found that the wastewater in the overground drainage led into the underground drainage inside the market and then flowed into the wells on the edge of the market. We then did a spot-check sampling across all the overground drains according to the principles described in the Methods (Extended Data Fig. 1 ). Excreta of the upper respiratory tract of infected humans and the potential animal waste would be mixed together into the overground drainage. Thus, these data suggested that either infected people and/or animals in the market contaminated the sewage or that the contaminated sewage may have further played a role in furthering the virus transmission within the case cluster in the market. The merchants' activities were assessed against the PCR results of the environmental samples. The sampling covered 19.8% (134/678) of the shops in the market (95% confidence interval (CI): 16.8-23.0%). Of the positive samples, 44 were distributed among 21 shops in the market, 19 of whom were located in the West Zone with the remaining two located in the east area (Fig. 1A ). Some vendors sold more than one type of product. While the results provided some indication of the association of cases with different products, no significant differences were observed between different shops, including those selling poultry (22%, 8/37: 95% CI: 9.8-38.2%), cold-chain products (18.4%, 16/87, 95% CI: 10.9-28.1%), aquatic products (17.8%, 13/73, 95% CI: 9.8-28.5%), livestock (14%, 5/36: 95% CI: 4.7-29.5%), seafood products (11%, 6/56: 95% CI: 4-21.9%), wildlife products (11%, 1/9: 95% CI: 0.3-48.2%), and vegetables (25%, 2/8: 95% CI: 3.2-65%) (Extended Data Fig. 2 , Extended Data Table 5 ). The detection of SARS-CoV-2 in multiple shops selling different product types suggested that SARS-CoV-2 may have been circulating in the market, especially the West Zone, for a while in December 2019, leading to an extensive distribution of the virus within the market, which may have been facilitated by the crowded buyers and the contaminated environment. The 457 animal samples included 188 individuals belonging to 18 species (with some stray animals sampled until March 30 th ) (Extended Data Table 6 ). The sources of the samples included unsold goods kept in refrigerators and freezers in the stalls of the HSM, and goods kept in warehouses and refrigerators related to the HSM. Three Chinese giant salamanders, which were found in a fish tank, were alive and swab samples were collected and tested. Samples from stray animals in the market were also collected, comprising swab samples from 10 stray cats, 27 samples of cat feces, one A C C E L E R A T E D A R T I C L E P R E V I E W dog, one weasel, and 10 rats. All the 457 animal samples tested negative for SARS-CoV-2 nucleic acid. To determine whether there was live virus in the HSM, we inoculated 27 SARS-CoV-2 positive environmental samples collected on January 1 st , 2020, into cell lines, including Vero E6 and Huh7.5 cells. Cytopathic effects (CPE) were observed 3 days post inoculation with sample Env_0313 on Vero E6 cells. CPE was also observed 5 days post inoculation on Huh7.5 cells. The electron micrographs of Vero E6 cells after 5 days of post inoculation showed that virus particles were present in both the supernatant and the cells. Negative-stained virus particles and ultra-thin cultured cell sections showed typical coronavirus morphology (Fig. 2). Live viruses were isolated from samples Env_0313, Env_0354 and Env_0126, which were the only three samples with CT values <30 in the PCR. Env_0354 and Env_0126 were swab samples from the ground and Env_0313 were swab samples from a wall. Notably, samples Env_0313 and Env_0354 were from the stalls with confirmed patients. All the results of successful virus isolation from the original samples with low CT values revealed the existence of live SARS-CoV-2 with high titers in the environment of the HSM. Do the high CT values, we did not perform virus isolation based on the samples collected from later time points due. During later sampling in the HSM in February, we collected samples to investigate the virus RNA persistence in the market. Some of these samples tested positive, especially in the sewage well and even on the walls (Supplementary Table 2). Within the 73 PCR positive samples, 35 samples (27 within the HSM and 8 from the surrounding area) collected in February were still positive for SARS-CoV-2. The long persistence of its genetic material in the environment might reflect high levels of environmental contamination before the market was closed. For the sample Env_0838, collected from a wall on February 20 th 2020, a 3-plex PCR test was performed. The viral RNA segment was undetectable in one PCR channel targeting N gene, but could be amplified in the A C C E L E R A T E D A R T I C L E P R E V I E W other two channels targeting the RdRp and E genes, with CT values of 32.59 and 37.34, respectively. This result is reasonable considering the degradation of the viral genome. However, the results also indicate a long persistence of the viral RNA in the environment. We further performed high-throughput sequencing (Supplementary Table 3 ) and successfully obtained seven complete or near complete SARS-CoV-2 genome sequences, including three sequences from three environmental samples (Env_0313, Env_0354 and Env_0020), and four sequences from cell supernatants of Env_0313, Env_0354 and Env_0126 (Fig. 3 , Supplementary Table 4 ). A few samples were resequenced using a multiplex PCR approach, including Env_0020_seq01, Env_0313_seq04, Env_0313_seq05, Env_0126_seq06, and Env_0354_seq07 (Supplementary Table 3 and 4 ). The genome sequences of three environmental samples, Env_0126, Env_0313 and Env_0354, were found to be completely identical to the reference strain HCoV-19/Wuhan/IVDC-HB-01/2019 (IVDC-HB-01, GISAID accession number: EPI_ISL_402119) and the human strain Wuhan-Hu-1 (GenBank: NC_045512) (Fig. 3A ). The genome sequence of the isolated virus from environmental sample Env_0354 had two synonymous mutations compared to HCoV-19/Wuhan/IVDC-HB-01/2019, with sequence identity of 99.99% (Fig. 3A ). Therefore, the SARS-CoV-2 sequences from environmental samples were highly similar to the clinical strains obtained during the early stages of the COVID-19 outbreak. Previously, SARS-CoV-2 has been proposed to be classified into two major lineages based on the two highly-linked single nucleotide polymorphisms (SNPs): A lineage (8782T and 28144C, or S lineage in another nomenclature of SARS-CoV-2) and B lineage (8782C and 28144T, or L lineage). It has been proposed that A/S lineage most likely is the ancestral lineage, because all of the SARS-CoV-2 related coronaviruses from bats and pangolins possessed 8782T and 28144C 25,26 , while Pekar et al. also presented a possibility that both lineages represent separate introduction events 27 . Phylogenetic analysis revealed that most of the environmental strains belong to the B/L lineage and they cluster together with the human strains circulating in the early stage of the pandemic (Fig. 3B , Supplementary Fig. 1 ). The phylogenetic analysis did not involve the environmental sample Env_0020, the A/S lineage of which was confirmed by the high number of reads mapped to positions 8782 and 28144 in Env_0020 (Supplementary Table 5 ). However, it should be noted that the genome of Env_0020 is of low quality and there are many discontinuous gaps in the assembled genome. Indeed, though it is difficult to root the SARS-CoV-2 phylogenetic tree, our analysis indicated that the environmental viruses clustered together with the human strains circulating in the early stages of the pandemic. We conducted RNA-seq analysis using 60 SARS-CoV-2 PCR-positive and 112 SARS-CoV-2 PCR-negative environmental samples from the HSM (Fig. 4A and Supplementary Table 3 ), in which the bias of sampling and RNA-seq should be considered. We used two approaches for genera identification. The Kraken2 method with all available genes/genomes in the database was used for the identification of all genera, including bacteria, viruses, eukaryota, and archaea. Additionally, the barcoding method using mitochondrial cytochrome c oxidase subunit I (COI) sequences was used specifically for the identification of Chordata genera. Bacteria were the most abundant species in almost all samples and mammal species could be found in most samples, which fit the feature of samples collected from the environment (Fig. 4B and Supplementary Table 6 and 7 ). Gallus, Homo, Anas, Sus, Bos, and Canis could be detected in most samples (Fig. 4C and Supplementary Table 8 ), which was in accordance with the environmental feature of the seafood markets in China. We analyzed the mammalian genera in all sequenced samples with kranken2 (detailed in the methods) using different thresholds. A total of 70 mammal genera, which existed in more than 2% samples, were identified with a threshold of 100 reads per million (Fig. 4D ). It is important to highlight that the results of the kraken2 analysis (Figure 4D ) and the BOLD analysis (Extended Data Figure 3 ) differ. In particular, the proportion of reads assigned as raccoon dog differ considerably with the two methods used. This may be due to the heterogeneity of the reference data used by the two methods (BOLD, as for mitochondria, and kraken2 for whole genome). It should be noted that the genera identified using current approaches might be updated with additional reference genomes. As such, this list is not definitive and further in-depth analysis with other methods will be required to provide more information regarding the wildlife species present at the market. Particularly, we analyzed three samples (Env_0126, Env_0313 and Env_0354) collected on 1 st Jan 2020 with high levels of SARS-CoV-2 (Ct value <30) (Fig. 4E ). The identified mammal genera in the Env_0313 and Env_0354 samples were related to species in the general food market, such as Homo, Ovis, Bos, Canis, Sus, and Felis. Many mammalian genera were observed in the Env_0126 sample, but the most abundant mammalian genera were also related to the general food market, including Bos (77.30%), Ovis (19.91%), Homo (0.77%), and Bubalus (0.57%). Pipistrellus (0.002%) and Lutra (0.001%) were found also found in this sample, but at extremely low relative abundance, raising the possibility of false detection. Moreover, we also noted that only Homo, Ovis, Bos, and Sus reads but not species related to wildlife were found in the Env_0020 samples, the one that belongs to the A/S lineage. We illustrated the top-ranked genera in four areas of the market, where multiple SARS-CoV-2 PCR-positive samples were detected. As shown in Fig. 4F , the top-ranked genera in these areas were homo or other genera that generally exist in food markets. We also noted that Nyctereutes could be found in the shop 25 of street 8, while Atelerix and Erinaceus could be found in shops 15-17 of street 7 (Fig. 4F ). These genera were detected in both SARS-CoV-2 positive and SARS-CoV-2 negative samples, and actually more often so in negative ones (Supplementary Recent reports traced the outbreak back to the HSM and proposed, after compiling information reported by various sources, including the WHO-China Joint Report and social media, etc. that the market sold live wild animals as recently as 2019 28 . Another report hypothesized that SARS-CoV-2 spilled over from animals to humans at least twice in November or December 2019, and the raccoon dog was hypothesized to be the intermediate host animal 27 . The evidence provided in this study is not sufficient to support such a hypothesis 29 . Our study confirmed the existence of raccoon dogs, and other hypothesized/potential SARS-CoV-2 susceptible animals, at the market, prior to its closure. However, these environmental samples cannot prove that the animals were infected. Furthermore, even if the animals were infected, our study does not rule out that human-to-animal transmission occurred, considering the sampling time was after the human infection within the market as reported retrospectively 6 . Thus, the possibility of potential introduction of the virus to the market through infected humans, or cold chain products, cannot be ruled out yet. A C C E L E R A T E D A R T I C L E P R E V I E W 13 More work, involving internationally coordinated efforts, is needed to investigate the potential origins of SARS-CoV-2 24 . Surveillance of wild animals should be enhanced to explore the potential natural and intermediate hosts for SARS-CoV-2 7,30 , if any, which would help to prevent future pandemics caused by animal-origin coronaviruses. A C C E L E R A T E D A R T I C L E P R E V I E W 14 References A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W The Huanan Seafood Market (HSM) was closed in the early morning of January 1st 2020, and at the same time, China CDC began collecting environmental and animal samples. Staff from China CDC entered the market about 30 times before the market's final clean-up on March 2 nd 2020, with some stray animals sampled outside the market until March 30 th . Environmental samples in the HSM were collected to represent exhaustively as possible, from a wide diversity of surfaces, animals and products (Supplementary Table 2 and Extended Data Table 6 ) according to different sampling For animal samples, depending on the type of animal and whether it was alive or frozen, pharyngeal, anal, body surface and body cavity swabs or tissue samples were collected for nucleic acid testing (NAT). Generally, for alive animal and frozen full bodies, three samples, including pharyngeal, anal and body surface swabs were collected for each animal individuals. And for animal bodies after "bai tiao" disposing (remaining parts of poultry or livestock after removal of hair and viscera), the body cavity swabs were collected. Drain samples were collected by the use of virus sampling swabs to probe into the silt at the bottom of drainage channels in the market. Wastewater and silt samples were preserved in virus preservation solution. For the sewage well (for the drain water), a container was used to take a silt-water mixture from a location near the bottom of the well, and an appropriate amount of sample was collected by using virus sampling swabs and then preserved in virus preservation solution. A virus nucleic acid extraction kit (Xi'an Tianlong) was used to extract viral nucleic acid from samples using an automated nucleic acid extraction instrument according to the manufacturer's instructions. Real-time (RT) PCR was performed on extracted nucleic acid samples with a SARS-CoV-2 nucleic acid assay kit. The reagent brands include BioGerm (40/38, cycle number/cut-off value, the same as below), DAAN (45/40) and BGI (40/38). Virus isolations Virus isolations were performed in biosafety level (BSL)-3 laboratory in National Institute for Viral Diseases Control and Prevention, China CDC. Samples positive for SARS-CoV-2 were cultured in Vero E6 and Huh7.5 cells on January 11 th , 2020. The cell lines were inoculated with positive samples and three blind passages were performed for each sample. The culture supernatant and cell pellet of each passage were harvested for RT PCR. The morphology of viral particles in the cell sections and the supernatant were firstly observed by transmission electron microscope (TEM) on January 22 nd , 2020. Metagenomic sequencing Metagenomic sequencing was conducted at National Institute for Viral Disease Control A C C E L E R A T E D A R T I C L E P R E V I E W and Prevention, China CDC and Wuhan BGI. Nucleic acid was extracted using Qiagen's viral RNA microextraction kit and human nucleic acid was removed using an enrichment kit to improve the sensitivity of viral RNA detection. Extracted RNA was reverse transcribed into cDNA and segmented into 150-200 bp by enzyme digestion. After repair, fitting, purification, PCR amplification and purification, sample concentration was assayed by DNBSEQ-T7, and an average output of more than 200 million reads was obtained. Sequencing data were compared with those in a SARS-CoV-2 database to determine whether the samples contained coronavirus sequences. For the seven complete SARS-CoV-2 genome sequences, three sequences from environmental samples (Env_0020_seq01, Env_0313_seq02 and Env_0354_seq03) were obtained from DNBSEQ-T7, and four sequences from cell supernatants of Env_0313, Env_0354 and Env_0126 (Fig. 3 ) were obtained from NextSeq 550 platform. A few samples were re-sequenced using a multiplex PCR approach, including Env_0020_seq01, Env_0313_seq04, Env_0313_seq05, Env_0126_seq06, and Env_0354_seq07 (Supplementary Table 3 and 4 ). All raw data related to the genomes, including any partial genomes that were sequenced were fully reported and deposited to the public database (Supplementary Table 3 and 4 ). Raw reads were adaptor-and quality-trimmed with the Fastp (version 0.20.0) program. The clean reads were mapped to the SARS-CoV-2 reference genome (GenBank: NC_045512) using Bowtie2. The assembled genomes were merged and checked using Geneious (version 11.1.5) ( https://www.geneious.com ). The coverage and depth of genomes were calculated with SAMtools v1.10 based on SAM files from Bowtie2. Reference genomes, IVDC-HB-01 (GISAID: EPI_ISL_402119) and Wuhan-Hu-1 (GenBank: NC_045512), were employed as a query. Multiple sequence alignment of the seven SARS-CoV-2 sequences obtained from this study and reference sequences were performed with Mafft (v7.450). Phylogenetic analyses were performed using RAxML v8.2.9 with 1000 bootstrap replicates, employing the GTR nucleotide substitution model and the Gamma distribution. All the raw sequencing data and genomes have been uploaded onto the GISAID (China CDC Weekly, 2021, DOI: 10.46234/ccdcw2021.255). The list of accession codes in Supplementary Table 3 and 4 A Extended Data Tables Extended Data Table 1. Overview of environmental sample sampling and testing in the Huanan Seafood Market. Extended Data Table 2. The collection logic of the environment samples. Extended Data Table 3. The collection logic of the animal samples. Extended Data Table 4. The information of the sampling in other markets. Extended Data Table 5. Twenty-one shops of RT-PCR positive in the Huanan Seafood Market. Extended Data Table 6. The animal samples collected in the Huanan Seafood Market. A C C E L E R A T E D A R T I C L E P R E V I E W Back Street Street 15 Back Street Street 13 Street 12 Street 10 Street 11 Street 9 Street 10 Street 8 Street 9 Street 7 Street 8 Street 6 Street 7 Street 5 Street 6 Street 4 Street 5 Street 3 Street 4 Street 2 Street 3 Stree Street 2 Venders Live viruses were isolated Environmental PCR + Environmental PCR -Sewers or sewerage wells PCR + Street 1 Sewers or sewerage wells PCR -Domesticated wildlife products Confirmed patient (N=1) N West Zone Xinhua Road East Zone Fazhan Road 2 0 2 0 / 1 / 1 2 0 2 0 / 1 / 5 2 0 2 0 / 1 / 1 0 2 0 2 0 / 1 / 1 5 2 0 2 0 / 1 / 2 0 2 0 2 0 / 1 / 2 5 2 0 2 0 / 1 / 3 0 2 0 2 0 / 2 / 4 2 0 2 0 / 2 / 9 2 0 2 0 / 2 / 1 4 2 0 2 0 / 2 / 1 9 2 0 2 0 / 2 / 2 4 2 0 2 0 / 2 / 2 9 2 0 2 0 / 3 / 5 2 0 2 0 / 3 / 1 0 2 0 2 0 / 3 / 1 5 2 0 2 0 / 3 / 2 0 2 0 2 0 / 3 / 2 5 2 0 2 0 / 3 / 3 0 0 30 60 90 120 500 600 Collection Date Number of samples Environmental samples ( Positive) Environmental samples ( Negative) Animal samples ( Negative ) A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W 1 st week in 2020 2 nd week in 2020 3 rd week in 2020 4 th week in 2020 52 th week in 2019 Human Environment Date Host B 5.0E-5 1 5000 10000 15000 20000 25000 29903 Synonymous mutations IVDC-HB-01 Env_0313-20|P1 Env_0313-21|P1 Env_0126|P3 5' 5' 5' 5' 5' Env_0354|P3 3' 3' 3' 3' 3' C18129T NC_045512 Env_0313|Original Env_0354|Original 5' 5' 5' 3' 3' 3' A G22801A E n v _ 0 3 5 4 |P 3 E n v _ 0 3 1 3 |O r ig in a l E n v _ 0 3 5 4 |O r ig in a l E n v _ 0 1 2 6 | P 3 E n v _ 0 3 1 3 -2 0 |P 1 Env_ 0313 -21|P 1 Genotype S Genotype L A C C E L E R A T E D A R T I C L E P R E V I E W Positively detected genus Negatively detected genus PCR (+) PCR(-) RNA-seq (+) PCR(-) RNA-seq (-) 73 SARS-CoV-2 PCR positive 850 SARS-CoV-2 PCR Negative RNA-seq library 923 environmental samples 60 passed library quality control 112 passed library quality control Classification/genus distribution Mapping to with kraken2 Mapping with barcode of life data system A D E F B C 60 SARS-CoV-2 PCR positive samples 0 100 Percentage A r c h a e a S A R S -C o V -2 H o m o V ir u s e s E u k a r y o ta B a c te r ia 80 60 40 20 112 SARS-CoV-2 PCR negative samples 0 Barcoding method 10 20 30 40 50 Gallus Homo Anas Lariscus Coturnix Aves Sus Tadorna Alcelaphus Sorex Canis Amaurornis Phasianus Bos Columba Microryzomys Rupicapra Rattus Spilopelia Casuarius Nyctereutes Rhizomys Glis Oryctolagus Lepus Ovis Martes Neomys Dacelo Crocidura Eliomys Felis Percent Positive Street 6 Vender 29-31-33: Street 8 Vender 25: Venders Environmental SARS-CoV-2 PCR+ Street 15 Street 13 Street 12 Street 11 Street 10 Street 9 Street 8 Street 7 Street 6 Street 5 Street 4 Street 3 Street 2 Street 1 N West Zone Env_0879 Env_0882 Env_0885 Env_0887 Env_0808 Env_0809 Env_0828 Env_0862 Env_0865 Env_0868 Env_0875 Env_0585 Env_0620 Env_0660 Env_0717 Env_0719 Env_0806 Env_0807 Env_0552 Env_0576 Env_0577 Env_0579 Env_0580 Env_0583 Env_0584 Env_0275 Street 4 Vender 24-26-28: Env_0087 Env_0088 Env_0090 Env_0096 Env_0014 Env_0015 Street 7 Vender 15-17,16-24: Env_0061 Env_0063 Env_0002 Env_0018 Env_0020 Env_0033 Env_0055 Genera Canis Homo Oryctolagus Atelerix Nyctereutes Rattus Vulpes Ovis Lutra Acomys Mus Leopoldamys Erinaceus Nannospalax Onychomys Felis Sciurus Heterocephalus Sus Bos Marmota Ictidomys Arvicola Chinchilla Pan Cavia Pipistrellus Tachyoryctes Fukomys Hystrix Octodon Capra Muntiacus Ochotona Lepus Rhizomys Mustela Ailuropoda Ursus Halichoerus Others Env_0126 (B5) Bos Ovis Homo Bubalus Sus Bison Canis others 1743095 448956 17326 12841 10610 8233 4129 9661 77.30% 19.91% 0.77% 0.57% 0.47% 0.37% 0.18% 0.43% Genera Read counts Percentage Env_0354 (F54) Homo Ovis Bos Sus Canis Felis Acomys others 8941 460 92 51 43 27 23 18 92.60% 4.76% 0.95% 0.53% 0.45% 0.28% 0.24% 0.18% Genera Read counts Percentage Env_0313 (F13) Homo Ovis Bos Canis Sus Felis Pan Mus 8860 363 181 152 89 40 8 3 91.38% 3.74% 1.87% 1.57% 0.92% 0.41% 0.08% 0.03% Genera Read counts Percentage Env_0020 (A20) Homo Ovis Bos Sus 437 40 17 6 87.40% 8.00% 3.40% 1.20% Genera Read counts Percentage A C C E L E R A T E D A R T I C L E P R E V I E W Extended Data Fig. 1 A C C E L E R A T E D A R T I C L E P R E V I E W Extended Data Fig. 2 A C C E L E R A T E D A R T I C L E P R E V I E W Extended Data Fig. 3 A C C E L E R A T E D A R T I C L E P R E V I E W Extended Data Fig. 4 A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W A C C E L E R A T E D A R T I C L E P R E V I E W nature portfolio | reporting summary For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section. n/a Confirmed The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section. A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable. For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above. Policy information about availability of computer code Data collection For RNA-seq, raw datasets were collected with the BGI's Sequencing Systems. Virus genome assembly and phylogenetic analysis Raw reads were adaptor-and quality-trimmed with the Fastp (version 0.20.0) program. The clean reads were mapped to the SARS-CoV-2 reference genome (GenBank: NC_045512) using Bowtie2. The assembled genomes were merged and checked using Geneious (version 11.1.5) ( https://www.geneious.com ). The coverage and depth of genomes were calculated with SAMtools v1.10 based on SAM files from Bowtie2. Reference genomes, IVDC-HB-01 (GISAID: EPI_ISL_402119) and Wuhan-Hu-1 (GenBank: NC_045512), were employed as a query. Multiple sequence alignment of the seven SARS-CoV-2 sequences obtained from this study and reference sequences were performed with Mafft v7.450. Phylogenetic analyses were performed using RAxML v8.2.9 with 1000 bootstrap replicates, employing the GTR nucleotide substitution model and the Gamma distribution. The Kraken2 (version 2.1.2) was used for species classification with the option '--confidence 0.1'. Sequences of all species in the Nucleotide (nt) database were used for generating the index. The bracken (version 2.5) was used for re-evaluating species abundance. The matrix of species was obtained by using the pavian algorithm. ggplot2 package in R was used for plotting. Read counts of each genus were used for further analysis and plotting. Raw counts of four domains (Archaea, Viruses, Eukaryota, and Bacteria), SARS-CoV-2, Homo genus, and Mammalia class were shown by heatmap. Two tail unpaired t-test was used for identification of differential genus between SARS-CoV-2 PCRpositive and -negative samples. For the analysis of the mammalian genus characterization, the reference was generated using the sequence of mitochondrial cytochrome c oxidase subunit I (COI-5P) in the barcode of life data (BOLD) system. RNA-seq samples were mapped to the reference sequences by the bowtie2 algorithm with the default settings. Read counts of each genus were calculated by the samtools. Read counts over 20 were used as