huanan-env-paper-private

For data and figures working towards the final paper

Sequences: quick links

• Viral sequences (bamboo rat CoV, raccoon dog amdovirus, civet kobuvirus): ./viruses/market_mammalian_viruses.fna
• Influenza H9N2 fragmented genome reconstructed from the market: ./viruses/Influenza.fasta
• mtDNA consensus genomes: ./MT_phylogenetics/lowconfidence_50_percent_mt_genomes.fasta
• BAMs of mtDNA mappings: ./MT_phylogenetics/bams_and_snvs/

Sample Metadata

./metadata/Liu_etal_2023_market_samples.tsv - Full metadata of all samples, including estimated geolocations.

./metadata/Liu_etal_2023_with_sequencing.csv - Full metadata of all samples, linking samples to their primary metagenomic (untargeted) sequencing runs.

./metadata/Sequencing_run_info.tsv - Information on the 184 sequencing runes in Liu et al.

./metadata/Liu_PCR_results.csv - PCR CT values reported by Liu et al.

By Figure

Figure 1

SARS2/20210903.WHO.masked.fasta - Sequences used in Fig 1 tree.

SARS2/Fig1_tMRCA.ipynb - plotting the tMRCA estimates.

SARS2/HSM_sequences/*.fa - consensus FASTA sequences for HSM SARS-CoV-2 genomes.

Figure 2: SARS2 abundances

./SARS2/count_reads_sars2.py - Script used to count the number of SARS-CoV-2 reads per sample.

./SARS2/sars2_reads_post_trimming.tsv - counts of SARS-CoV-2 reads in each sample.

./R/Fig2ABC.R and ./R/Fig2DEFGH.R - Scripts to plot the different panels of Figure 2.

Figure 2/3: mtDNA abundances

./mtDNA/clustering98.py - Script for first clustering the MT reference database at 98% identity.

./mtDNA/clustering93.py - Script for clustering the MT reference database at 93% identity.

./mtDNA/count_reads98.py - Script for counting mtDNA reads after mapping to the 98% clustered database.

./mtDNA/count_reads93.py - Script for counting mtDNA reads after mapping to the 93% clustered database (final species-level assignments).

./mtDNA/mitochondria_dereplicated93_final.fasta.gz - the final 93% ANI dereplicated database used in this study.

./mtDNA/mitochondrial_metazoa_counts_93.tsv - Read counts for animal mtDNA.

./mtDNA/mitochondrial_metazoa_coveredbases_93.tsv - Covered bases count for animal mtDNA

./mtDNA/species_descriptions_with_common_name.csv - Descriptions of species detected in this study.

./R/Fig3A and ./R/FigBCDE.R - Scripts to plot the different panels of Figure 3.

Figure 4: viruses

./viruses/Influenza.fasta - consensus Influenza H9N2 sequences identified in this study.

./viruses/count_reads_viral.py - Script for filtering and counting reads mapped to the viral database.

./viruses/filtered_viral_counts_97_95_20_200.tsv - counts of mapped viral reads.

./viruses/market_mammalian_viruses.fna - FASTA files of the consensus genomes assembled for mammalian viruses from the market.

./viruses/plant_insect_phage_exclude.txt - List of viruses to ignore due to being phage / plant / insect viruses.

./viruses/viral_metadata.tsv - Metadata on various viruses.

./viruses/cluster_viral_references.py - Script to cluster the viral reference database.

./viruses/get_viral_consensus.py - Script to reconstruct viral consensus genomes from multiple samples.

./viruses/viral_db.list.txt - a list of all viral sequences included in the dereplicated mapping database.

./R/Fig4ABC.R - Script to plot panels A-C of Figure 4.

Figure 5: mtDNA phylogenetics

./MT_phylogenetics/bams_and_snvs - All mapped mammalian mtDNA BAMs from market samples.

./MT_phylogenetics/MT_Maps.ipynb - Script to create Figure 5a mtDNA genome maps.

./MT_phylogenetics/mt_consensus_genomes.py - Script to reconstruct mtDNA consensus genomes.

./MT_phylogenetics/lowconfidence_50_percent_mt_genomes.fasta - MT genomes obtained in this study, requiring just 1x read coverage.

./MT_phylogenetics/mediumconfidence_50_percent_mt_genomes.fasta - MT genomes obtained in this study, requiring 3x read coverage to call a base.

./MT_phylogenetics/mtDNA_RD_phylogenetics.clean.ipynb - Raccoon dog phylogenetics analysis notebook.

./MT_phylogenetics/raccoon_dog_cytB_all.duplicated.fasta - Raccon dog reference cytB alignment.

Supplementary: rRNA analysis

./mtDNA/rRNA/count_reads93_rRNAs.py - Script to count mtDNA reads ignoring rRNA regions.

./mtDNA/rRNA/mt93_counts_rrna.tsv - Read counts ignoring rRNA regions.

./mtDNA/rRNA/rRNA_analysis.ipynb - Script to identify rRNA regions.

./mtDNA/rRNA/rrna_positions.tsv - positions of rRNA genes in the MT genomes.

Supplementary: Correlations

./correlations/Correlation.ipynb - Script to calculate correlations between animal sequence read abundances and SARS-CoV-2.

He et al. 2022 Cell data: Animal data from other markets

./HeCell2022/ - location of these files

He2022_metadata.csv - Metadata about all of the files from that study

cell2022_lowconfidence_mitochondria.fasta - FASTA file of consensus mitochondrial genomes with at least 1 read covering each position.

cell2022_mediumconfidence_mitochondria.fasta - FASTA file of consensus mitochondrial genomes with at least 3 reads covering each position.

./scripts/mt_consensus_genomes_He2022.py - script used to generate Mitochondrial genomes above

game_animals.xlsx - Additional metadata from He et al. 2022.

FASTQ processing

./data/fastq_processing/ - data related to FASTQ files

all_adapters.fa - list of adapters used for trimming

frequent_adapter_summary.tsv - results of adapter trimming, 5 most common adapters per library.

run_bbduk.sh - List of BBDuk commands run for each file for trimming.

./bbduk_results/*.txt - Full adapter trimming output for each file.