Cut adapt results in empty files

I am follwing the PacBio CCS Amplicon SOP v1 for Qimme2 and I can't seem to get cut adapt to work. The command runs but the output files are empty, the naming + location is correct.

Input:

mkdir trimmed_reads/

parallel -j 4 'cutadapt -g AGRGTTTGATCMTGGCTCAG...TACGGYTACCTTGTTACGACTT
--discard-untrimmed --no-indels -j 1 -m 1200 -M 1800
-o trimmed_reads/{/.}_trim.fastq {}'
::: raw_data_cat/*_cat.fastq

Output:

=== Adapter 1 ===

Sequence: TACGGYTACCTTGTTACGACTT...AGRGTTTGATCMTGGCTCAG; Type: linked; Length: 22+20; 5' trimmed: 0 times; 3' trimmed: 0 times
This is cutadapt 4.9 with Python 3.9.19
Command line parameters: -g TACGGYTACCTTGTTACGACTT...AGRGTTTGATCMTGGCTCAG --discard-untrimmed --no-indels -j 1 -m 1200 -M 1800 -o trimmed_reads/2314_16S_02_SD_2.49_388_cat_trim.fastq raw_data_cat/2314_16S_02_SD_2.49_388_cat.fastq
Processing single-end reads on 1 core ...
Finished in 1.325 s (26.286 µs/read; 2.28 M reads/minute).

=== Summary ===

Total reads processed: 50,424
Reads with adapters: 0 (0.0%)

== Read fate breakdown ==
Reads that were too short: 52 (0.1%)
Reads that were too long: 0 (0.0%)
Reads written (passing filters): 0 (0.0%)

Total basepairs processed: 75,624,156 bp
Total written (filtered): 0 bp (0.0%)

I've also been sent this message from the sequencing facility but I do not understand how to incorporate this into my code: "There are not adapters in the data. The data only has primer sequences. The adapters are removed during demultiplexing. I would suggest not using cutadapt for primer trimming as well. Within your cutadapt you are using –p-adapter twice whereas the data is single ended. If you want to continue using cutadapt, I suggest putting … between forward and reverse primer – like --p-adapter AGRGTTTGATCMTGGCTCAG…TACGGYTACCTTGTTACGACTT. That way cutadapt knows it must look for both the primers in the same single ended sequence. Within qiime dada2 denoise-ccs there is an option to specify –p-front parameter (forward primer) and –p-adapter (reverse primer). You can directly use that to remove primers and denoise the data."

Thank you!

Hello Tino,

Thank you for bringing this question to the forums!

First, I want to clarify that the SOP is from the LangilleLab Langille Lab · GitHub
I can still help out with the Qiime2 part and offer some general advice.

I concur with the advice from the sequencing core:

You can skip this step!

You can also do basic read trimming with DADA2, as mentioned here:

Here is the documentation for qiime dada2 denoise-ccs so you can learn more:
https://docs.qiime2.org/2024.5/plugins/available/dada2/denoise-ccs/

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Hey Colin, Thanks so much for the reply. Sounds like going through denoising will do the trick for me.

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