Marker data

Either clone the THAPBI PICT source code repository, or decompress the latest source code release (.tar.gz file). You should find it contains a directory examples/recycled_water/ which is for this example.

Shell scripts setup.sh and run.sh should reproduce the analysis discussed.

The documentation goes through running each step of the analysis gradually, including building a custom database, before finally calling pipeline command to do it all together. We provide script run.sh to do the final run-though automatically, but encourage you to follow along the individual steps first.

FASTQ data

File PRJNA417859.tsv was download from the ENA and includes the FASTQ checksums, URLs, and sample metadata. With a little scripting to extract the relevant sample metadata for use with THAPBI PICT this was reformatted as metadata.tsv (see below).

Script setup.sh will download the raw FASTQ files for Redekar et al. (2019) from https://www.ebi.ac.uk/ena/data/view/PRJNA417859 - you could also use https://www.ncbi.nlm.nih.gov/bioproject/PRJNA417859/

It will download 768 raw FASTQ files (384 pairs), taking about 4.8GB on disk

If you have the md5sum tool installed (standard on Linux; we suggest conda install coreutils to install this on macOS), verify the FASTQ files downloaded correctly:

$ cd raw_data/
$ md5sum -c MD5SUM.txt
...
$ cd ..

There is no need to decompress the files.

Amplicon primers & reference sequences

A region of ITS1 was amplified using the ITS6/ITS7 primer pair (GAAGGTGAAGTCGTAACAAGG and AGCGTTCTTCATCGATGTGC) which bind the 5.8S rDNA, described here:

Cooke et al. (2000) A molecular phylogeny of Phytophthora and related oomycetes. https://doi.org/10.1006/fgbi.2000.1202

The left primer (ITS6) matches the THAPBI PICT default, but their right primer (ITS7) matches about 60bp further downstream in Phytophthora. This means we can use THAPBI PICT default settings and get meaningful but blinkered results (for the subset of the data which our narrower primer set would have amplified, using a Phytophthora centric database).

In order to classify beyond Phytophthora, we need to build a THABPI PICT database including Pythium and Phytopythium. Redekar et al. (2019) Supplementary Table 3 provides a list of 1454 unique accessions and the species they assigned to it (not always the same as that listed on the NCBI record, as those annotations can change). Looking at those sequences, bar a handful they extend though the right primer. However, only about 50 have the left primer sequence included (depending how stringent you are), and the rest are also missing the next 32bp.

The ITS6 primer is situated within a highly conserved region, and the next 32bp is highly conserved, usually TTTCCGTAGGTGAACCTGCGGAAGGATCATTA. Unfortunately, the majority of published Oomycetes ITS1 sequences omit this. For the curated Phytophthora in the THAPBI PICT default database, we have inserted the expected sequence - and have yet to find a counter example. However, Redekar et al. (2019) took the other obvious choice, and remove it from their reads:

trimming extra bases from read1: an additional 32 bases from the 5′ end of read1, which mapped to 18S segment, were trimmed as the oomycete ITS reference database does not include the 18S segment;

We can do something similar in THAPBI PICT by treating this typically conserved 32bp region as part of the left primer - requiring it be present (while allowing some ambiguity) and removing it - leaving a shorter fragment which can be matched to a database built of those 1454 accessions.

Metadata

The provided file metadata.tsv has seven columns:

  1. Source, “Reservoir”, “River” or “Runoff”

  2. Site, “A”, “B”, “C”, …, “M”

  3. Process, “Filtration” or “Leaf baiting”

  4. Period, “01” to “28”

  5. Year-Month, “2015-04” to “2016-05” (given as “YYYY-MM” for sorting)

  6. Sample, author’s sample name, e.g. “OSU484”

  7. Accession, assigned by the public archive, e.g. “SRR6303585”

When calling THAPBI PICT, the meta data commands are given as follows:

$ thapbi_pict ... -t metadata.tsv -x 7 -c 1,2,3,4,5,6

Argument -t metadata.tsv says to use this file for the metadata.

The -x 7 argument indicates the filename stem can be found in column 7, Accession.

Argument -c 1,2,3,4,5,6 says which columns to display and sort by (do not include the indexed column again). If for example the accession was listed first, it would be sorted on that, which is not helpful here. If you prefer to sort on site first, or by date before process, this should be straightforward.

We have not given a -g argument to assign colour bands in the Excel reports, so it will default to the first column in -c, meaning we get three coloured bands for “Reservoir”, “River” and “Runoff”.

Other files

Files Redekar_et_al_2019_sup_table_3.tsv (plain text tab separated table) and Redekar_et_al_2019_sup_table_3.fasta (FASTA format) are based on the Excel format Supplementary Table 3 from the paper.