Analysis of eukaryotic ITS short-read amplicon sequences, including OTU clustering, taxonomic identification and abundance profiling, tree construction, pairwise dissimilarity metrics, MDS and various visualizations. The client provides raw amplicon sequence data and sample metadata.
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▾ General introduction
Fungal ITS metabarcoding is a genetic technique for surveying fungal diversity in a variety of environments, ranging from the ocean to soil and plant rhizospheres.
The internal transcribed spacer (ITS) region of the eukaryotic rRNA operon contains two highly variable spacers, ITS1 and ITS2,
each of which are popular marker genes for identifying fungal taxa and for estimating their relative abundances in samples.
In a single teaspoon of soil, for example, ITS metabarcoding can identify hundreds of distinct fungal species, yielding a high-resolution fungal blueprint of each sample that can be used for statistical comparisons across treatments, space or time, for visualization of local biodiversity, or for the detection of potential plant pathogens.
Due to its relatively low cost and practicality, ITS metabarcoding can easily be used in environmental surveys comprising hundreds to thousands of samples.
A typical ITS metabarcoding study proceeds as follows:
Collection of small amounts (<1 g) of material from each sample by the researcher.
Extraction of DNA from each sample using an in-house or commercial kit. This step is sometimes outsourced to an academic or commercial service provider.
Amplification of DNA fragments belonging to either the ITS1 or ITS2 gene using PCR, library preparation and sequencing of the amplified DNA. This step is commonly performed by an academic or commercial service provider. The most widespread technology is short read Illumina sequencing, which yields large numbers of sequences around 150-300 bp long.
Sequencing ultimately yields a separate set of DNA sequences for each sample, all covering the same region of the ITS1 or ITS2 gene, ranging from thousands to millions of sequences per sample. These data are commonly stored in fastq files, which are delivered by the sequencing service provider to the researcher.
Computational analysis of the sequences, including trimming and removal of poor quality (i.e., likely erroneous) sequences, clustering of similar sequences to reduce redundancy and identify species-like units called OTUs and strain-like units called ASVs, and estimation of the relative abundance of each OTU/ASV/taxon in each sample.
Statistical analysis, hypothesis testing and visualization of fungal community compositions. This step generally incorporates additional sample metadata, such as information about treatment groups, chemical measurements at each site, disease symptoms in plants, and so on.
We are eager to help you with your data analysis. Simply configure the analysis to your preferences, upload your sequences and metadata, and we can handle it from there.
▸ Overview of provided analysis
Our analysis starts with raw short-read Illumina ITS1 or ITS2 gene amplicon sequences, which are provided by the client and typically obtained from a sequencing service provider.
We deliver a summary report and key data products for presentations and downstream investigations.
Main steps and deliverables:
Basic quality filtering and trimming of sequences to improve overall data quality.
Inference of amplicon sequence variants (ASVs) using dada2 and OTU clustering at a user-specified similarity threshold using vsearch.
Optionally, chimeras may be detected and removed, a phylogenetic tree constructed for the ASVs, and ASVs mapped to the UNITE ITS database to find closest matches.
ASVs and OTUs are taxonomically classified using a consensus approach based on the Unite ITS reference database.
ASV and OTU tables are computed (TSV and BIOM format), listing the estimated relative abundances of each ASV and OTU in each sample.
Calculation of richness, Shannon-entropy and other α-diversity metrics for each sample and at each taxonomic level.
Multiple common pairwise dissimilarity metrics (aka. β-diversities) are computed between samples, measuring the differences in taxonomic compositions at various taxonomic levels.
Two-dimensional multidimensional scaling is performed based on the pairwise dissimilarities.
Common visualizations, such as barplots of relative ASV/OTU/taxon abundances, MDS plots.
In addition, we also provide a thorough Materials & Methods writeup for use in your publications.
▸ Input requirements
All sequence data must be generated on the same Illumina platform (for example, MiSeq or HiSeq2000), targeting either the ITS1 or the ITS2 gene using the same set of primers.
Sequence data must be provided as demultiplexed fastq files, one file per sample and per read direction. For paired-end reads, you will thus need to provide two fastq files.
Metadata must be provided for all samples in the form of a table file (e.g. CSV). This table must at the very least specify sample IDs and the fastq file names for each sample.
▸ Examples of data products
OTU_representative_sequences.fasta
Fasta file listing representative DNA sequences of inferred OTUs.
OTU_abundance_table.tsv
OTU abundance table, specifying the abundances (numbers of reads mapped) for each OTU in each sample.
OTU_taxonomic_assignments.tsv
Table listing the estimated taxonomic classifications of OTUs.
Genus_abundance_table.tsv
Table listing abundances (number of reads mapped) for each genus in each sample.
Dissimilarity_matrix_OTU_Jaccard.tsv
Table listing pairwise Jaccard dissimilarities between samples, in terms of their OTU proportions.
Tree_OTU_abundance_jaccard.tre
Hierarchical clustering tree of samples based on their pairwise Jaccard dissimilarities at OTU level.
▸ Examples of generated figures
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▸ Used 3rd party resources
Main databases and software used in this analysis:
Habibi-Soufi, H., Tran, D., Louca, S. (2024). Microbiology of Big Soda Lake, a multi-extreme meromictic volcanic crater lake in the Nevada desert. Environmental Microbiology 26:e16578
Schoch, L. S., Seifert, A. S., Huhndorf, H., Robert, R., Spouge, L. S., Levesque, A. L. et al. (2012). Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proceedings of the National Academy of Sciences 109:6241-6246
▸ Price and billing
Price starts at $50 base + $5 per sample. Final price may differ depending on user settings, and will be available prior to order submission. Log in to see availability and payment modalities.
