The SILVA database project provides comprehensive, quality checked and regularly updated databases of aligned small (16S / 18S, SSU) and large subunit (23S / 28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukarya).

These DADA2-formatted training fasta files were derived from the Silva Project's version 138 release. See https://www.arb-silva.de/documentation/release-138/ for database and citation information. The Silva 138 database is licensed under Creative Commons Attribution 4.0 (CC-BY 4.0); see file "SILVA_LICENSE.txt". The fasta files were generated and checked for consistency with version 132 using the R code in the R-markdown document "silva-v138.Rmd".

16S metabarcoding databases and naive-bayes classifiers specific to the V4-V5 region. Built from the Silva 138.1 SSU Ref NR 99 database using Qiime2 (version 2023.2) and the q2-clawback plugin. Includes weighted classifiers for two Earth Microbiome Project Ontology (EMPO) 3 habitat types: "sediment (saline)" and "water (saline)" , with data downloaded from Qiita. Sequences were dereplicated with Rescript --p-mode 'uniq' , retaining identical sequence records that have differing taxonomies.

Primers used:

EMP 16S 515f: GTGYCAGCMGCCGCGGTAA

EMP 16S 926r: CCGYCAATTYMTTTRAGTTT

Stats

286,948 unique sequences

309,567 total sequences

46,254 unique taxa (Level 7)

SILVA release 132 and 138 non-redundant (clustered at 99%) database including typestrains in both ARB and UDB (usearch11) formats. For use with https://github.com/KasperSkytte/AutoTax

Uniform and weighted naive Bayes classifiers trained on Silva 138.1 data for use with QIIME 2 q2-feature-classifier.

full-length-average-classifier.qza and 515f-806r-average-classifier.qza are classifiers using weights averaged across 14 EMPO 3 habitat types. If in doubt, use one of these.

Original weights derived from Qiita, scripts used to derive them, and additional information available at https://github.com/BenKaehler/readytowear.

Classifiers trained on full-length 16S or 515F/806R region as labelled.

Full length Silva 138.1 reference sequences and corresponding taxonomies are in ref-seqs.qza an ref-tax.qza.

If you use any of the weighted classifiers, please cite

• Kaehler BD, Bokulich NA, McDonald D, Knight R, Caporaso JG, Huttley GA. (2019). Species-level microbial sequence classification is improved by source-environment information. Nature Communications 10: 4643. doi: https://doi.org/10.1038/s41467-019-12669-6

If you use the any of the classifiers (weighted or otherwise), please cite

• Bokulich, N.A., Kaehler, B.D., Rideout, J.R. et al. (2018). Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 90. doi: https://doi.org/10.1186/s40168-018-0470-z

If you use any file from here, please cite:

• Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596

• Robeson, M. S., O’Rourke, D. R., Kaehler, B. D., Ziemski, M., Dillon, M. R., Foster, J. T., & Bokulich, N. A. (2021). RESCRIPt: Reproducible sequence taxonomy reference database management. PLoS Comp. Bio., 17(11). doi: https://doi.org/10.1371/journal.pcbi.1009581

Warning: Pre-trained classifiers that can be used with q2-feature-classifier currently present a security risk. If using a pre-trained classifier such as the ones provided here, you should trust the person who trained the classifier and the person who provided you with the qza file.

These training fasta files are derived from the Silva Project's version 138.1 release and formatted for use with DADA2. These files are intended for use in classifying prokaryotic 16S sequencing data and are not appropriate for classifying eukaryotic ASVs.

See https://benjjneb.github.io/dada2/training.html for information about DADA2 reference databases and https://www.arb-silva.de/documentation/release-138.1/ for database and citation information for Silva 138.1. The Silva 138.1 database is licensed under Creative Commons Attribution 4.0 (CC-BY 4.0); see file "SILVA_LICENSE.txt". These fasta database files were generated and checked for consistency using the R markdown documents in the silva-138.1 folder in https://zenodo.org/record/4587946.

If you use these files, please cite one or both of the Silva references below (or at the above link) and the DADA2 paper (reference below). I also recommend citing or linking to the Zenodo record for this specific version in your Methods or published source code to record the specific taxonomic database files used in your analysis.

NOTE: These database files have a known problem in 3/895 families and 59/3936 genera. See https://github.com/mikemc/dada2-reference-databases/blob/main/silva-138.1/v1/bad-taxa.csv for a list of affected taxa and https://github.com/benjjneb/dada2/issues/1293 for more information.

Training set for Silva 138.1 for use with the IDTAXA taxonomy caller within the R DECIPHER packageCitation for DECIPHER: Wright ES (2016). “Using DECIPHER v2.0 to Analyze Big Biological Sequence Data in R.” The R Journal, 8(1), 352-359.

Modified version (BLASTn & BLCA ready) of the file SILVA_138.1_SSURef_tax_silva_trunc.fasta.gz for ngs4ecoprod (https://github.com/dschnei1/ngs4ecoprod). Further details of the preparation procedure can be found in README.txt within the archive (silva_NR99_138.1.tar.gz). Original file: https://www.arb-silva.de/fileadmin/silva_databases/release_138.1/Exports/SILVA_138.1_SSURef_NR99_tax_silva_trunc.fasta.gz If you use this database please cite the original authors of the SILVA database: Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596 doi: 10.1093/nar/gks1219 The SILVA databases are licensed under Creative Commons Attribution 4.0 (CC-BY 4.0): https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/legalcode

Modified version (BLASTn & BLCA ready) of the file SILVA_138.2_SSURef_tax_silva_trunc.fasta.gz. Further details of the preparation procedure can be found in README.txt within the archive (SILVA_138.2_SSURef_NR99.tar.gz). Original file: https://www.arb-silva.de/fileadmin/silva_databases/release_138_2/Exports/SILVA_138.2_SSURef_NR99_tax_silva_trunc.fasta.gz If you use this database please cite the original authors of the SILVA database: Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596 doi: 10.1093/nar/gks1219 The SILVA databases are licensed under Creative Commons Attribution 4.0 (CC-BY 4.0): https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/legalcode

metadata and silva classifier

16S metabarcoding databases and naive-bayes classifier specific to the V4-V5 region. Built from the Silva 138.1 SSU Ref NR 99 database using Qiime2 (version 2021.2).

Primers used:

EMP 16S 515f: GTGYCAGCMGCCGCGGTAA

EMP 16S 926r: CCGYCAATTYMTTTRAGTTT

File description







          File
          Description




          silva-138-99-seqs.qza
          Full length Silva 138.1 SSU 99 sequences


          silva-138-99-tax.qza
          Taxa for full length Silva 138.1 SSU 99 database


          refseqs_V4-V5.qza
          Sequences for 16S V4-V5 (primers 515f, 926r), extracted from Silva 138.1 SSU 99, generated by qiime2-2021.2 (forward compatible)


          classifier_V4-V5.qza
          Unweighted (uniform) naive-bayes classifier for 16S V4-V5 (primers 515f, 926r) extracted from Silva 138.1 SSU 99, generated by qiime2-2021.2

Improved version of the SILVA microbial taxonomic database version 138 NR99 as processed through AutoTax, see reference paper.

These DADA2-formatted training fasta files were derived from the Silva Project's version 138.2 release: https://www.arb-silva.de/

These fastas were generated by the following commands (using the dada2 R package version 1.35.4):

path <- "~/tax/Silva/v138_2"
fn.out.slv <- "~/Desktop/silva_nr99_v138.2_toGenus_trainset.fa.gz"
dada2:::makeTaxonomyFasta_SilvaNR(file.path(path, "SILVA_138.2_SSURef_NR99_tax_silva.fasta.gz"),
file.path(path, "tax_slv_ssu_138.2.txt"),
fn.out.slv)

fn.out.spc.slv <- "~/Desktop/silva_nr99_v138.2_toSpecies_trainset.fa.gz"
dada2:::makeTaxonomyFasta_SilvaNR(file.path(path, "SILVA_138.2_SSURef_NR99_tax_silva.fasta.gz"),
file.path(path, "tax_slv_ssu_138.2.txt"),
fn.out.spc.slv, include.species=TRUE)

fn.out.aS.slv <- "~/Desktop/silva_v138.2_assignSpecies.fa.gz"
dada2:::makeSpeciesFasta_Silva("~/tax/silva/v138_2/SILVA_138.2_SSURef_tax_silva.fasta.gz",
fn.out.aS.slv)

Taxonomic classification of the 16S rDNA sequencing reads was performed using QIIME2, referencing the SILVA 138 database, at the Phylum, Class, Order, Family, and Genus levels.

PRJNA860062 Assigned Taxonomy: This upload comprises two datasets with the assigned taxonomy for sequence variants of BioProject PRNJA860062. PRJNA860062_ASVCounts_NCBItaxonomy.txt PRJNA860062_ASVCounts_SILVAtaxonomy.txt BioProject PRNJN860062 compares bacterial profiles of zebrafish larvae microbiota resulting from two different microbial colonization methods. The full description and sequence data for this project can be obtained from the Sequence Read Archive (https://www.ncbi.nlm.nih.gov/bioproject). The dataset with the SILVA taxonomy can directly be obtained using the QIIME2 script included in this upload ('PRJNA860062_QIIME2Script.txt'). As previously noted by Lesack and Birol (2018), SILVA species annotations include nomenclature errors (DOI: 10.1101/441576). Therefore, the dataset with the NCBI taxonomy comprises a manually corrected taxonomy for BioProject PRNJA860062, based on the family to phylum level nomenclature of the NCBI taxonomy browser (https://www.ncbi.nlm.nih.gov/taxonomy). Both files are tab-delimited text files, include the domain to species level taxonomy in the first 7 columns, and include the number of assigned sequence variants (ASVs) per taxon in the final 6 colums, corresponding to BioSample SAMN29820940, SAMN29820941, SAMN29820942, SAMN29820943, SAMN29820944, and SAMN29820945. QIIME 2 Pipeline: The QIIME2 script that was used to obtain the assigned SILVA taxonomy BioProject PRNJA860062 is uploaded as: PRJNA860062_QIIME2Script.txt Input files that are required to run this script, including a manifest text file, sample metadata, and the reference sequences and taxonomy from the SILVA 138 small subunit (16S/18S) rRNA database Ref NR 99, are uploaded in the zipped file: PRJNA860062_InputFiles.zip FASTQ sequence data for BioSample SAMN29820940, SAMN29820941, SAMN29820942, SAMN29820943, SAMN29820944, and SAMN29820945, can be obtained from the Sequence Read Archive under BioProject PRNJA860062 (https://www.ncbi.nlm.nih.gov/bioproject). All output files are uploaded in the zipped file: PRJNA860062_OutputFiles.zip Data provenance, including the versions of python (3.6.7) and python packages, can be acquired by dragging QIIME2 Visualizations (.qzv output files) into the QIIME2 viewing interface (http://view.qiime2.org).

Modified version (blastn ready) of the file SILVA_138.1_SSURef_NR99_tax_silva_trunc.fasta.gz for NGS-4-ECOPROD pipeline.

See https://www.arb-silva.de/no_cache/download/archive/release_138.1/Exports/

SILVA references:

Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl. Acids Res. 41 (D1): D590-D596.

Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, Schweer T, Peplies J, Ludwig W, Glöckner FO (2014) The SILVA and "All-species Living Tree Project (LTP)" taxonomic frameworks. Nucl. Acids Res. 42:D643-D648

Glöckner FO, Yilmaz P, Quast C, Gerken J, Beccati A, Ciuprina A, Bruns G, Yarza P, Peplies J, Westram R, Ludwig W (2017) 25 years of serving the community with ribosomal RNA gene reference databases and tools. J. Biotechnol.

Usearch formatted silva v138 converted from dada2-format (from here: https://zenodo.org/record/3731176#.XqsLVBNKhqU)

Tutorial output for the Tourmaline amplicon sequence processing workflow.

Tourmaline was run on the test data provided in the directory 00-data, which were downloaded along with the rest of the repository using this command:

git clone https://github.com/aomlomics/tourmaline

Reference data were downloaded and symlinked using these commands:

cd tourmaline/01-imported wget https://data.qiime2.org/2021.2/common/silva-138-99-seqs-515-806.qza wget https://data.qiime2.org/2021.2/common/silva-138-99-tax-515-806.qza ln -s silva-138-99-seqs-515-806.qza refseqs.qza ln -s silva-138-99-tax-515-806.qza reftax.qza

Paths in 00-data/manifest_pe.csv and 00-data/manifest_se.csv were edited to match the local paths.

Output for all modes of the workflow were then generated in series:

conda activate qiime2-2021.2 snakemake dada2_pe_report_unfiltered snakemake dada2_pe_report_filtered snakemake dada2_se_report_unfiltered snakemake dada2_se_report_filtered snakemake deblur_se_report_unfiltered snakemake deblur_se_report_filtered

In a recent manuscript, we report a draft genome of the ascomycotal fungal species Pseudopithomyces maydicus (isolate name SBW1) obtained using a culture isolate from brewery wastewater. From a 22 contig assembly, we predict 13502 protein coding gene models, of which 4389 (32.5%) were annotated to KEGG Orthology and identify 39 biosynthetic gene clusters. Here we provide supplementary data from our analysis:

Supplementary Figure 1
Sequence alignment between Sanger-sequenced partial 28S LSU-rRNA sequence and the top ranked BLASTN hit from NCBI nr/nt database.

Supplementary Figure 2
Pairs plot for contig GC-content, contig coverage and contig length from the P. maydicus assembly.

Supplementary Data File 1
Table listing properties of contigs from the P. maydicus assembly.

Supplementary Data File 2
Summary of taxonomic classification analysis of recovered 18S SSU-rRNA sequences to the SILVA 138 database.

Supplementary Data File 3
Alignment of Sanger-sequenced partial 28S LSU-rRNA sequence against three 28S LSU-rRNA gene sequences recovered from the P. maydicus long read genome assembly and a set of 62 28S LSU-rRNA sequences from members of genus Psuedopithomyces (NCBI Nucleotide searched for “Pseudopithomyces AND 28S" on 30th May 2022).

Supplementary Data File 4
MASH similarity statistics obtained by comparing the P. maydicus long read genome assembly sequence to 9563 fungal genomes obtained from NCBI. The reference genomes from NCBI were downloaded using the NCBI ‘dataset’ (version 13.6.0) command line tool (datasets_13.6.0 download genome taxon 4751 --filename fungi.zip --assembly-level complete_genome,chromosome,scaffold,contig --exclude-gff3 --exclude-protein --exclude-rna).

Supplementary Data File 5
BlastKOALA annotation data for all proteins predicted from P. maydicus long read assembly.

Supplementary Results
Complete output from the antiSMASH6 analysis of the P. maydicus long read assembly.

SILVA v138 DB for use in BIOL 351 lab teaching