Human Skin WGS Metagenome Sequence Quality Control
I am trying to generate relative abundances of bacteria using Kraken2 given in a set of human skin WGS Metagenomic sequences (sequenced using Illumina NovaSeq 6000; Library Construction Protocol:Illumina Nextera XT). I am carrying out quality control now and have the following questions regarding it,
- I carried out trimming of adapter sequences and low quality bases with trimmomatic (adapter source file - NexteraPE-PE.fa). However, the first 20 bp of the reads still exhibit a bias (images below of per base sequence content) that was there before trimming. Initially, I thought this was from adapters but it doesn't seem to be the case. What could be the reason for this bias? Is it advisable to clip them?
Before trimming
After trimming
2a. When it comes to metagenomic sequences, since we have microbial genomic sequences do we expect the percent GC content to deviate from a normal distribution?
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The two plots before and after trimming are identical, which makes me think that nothing was trimmed.
It is a safe bet that GC content will not have a normal distribution, unless the community is of low complexity. For an example, see Figure 5 of the following paper:
https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2015.01044/full
See also Figure 2 of this paper:
https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2013.00084/full
Thank you for the reply and the references.
More than likely it is just the positional bias because of random priming/tagmentation during library prep. You can read more about it in this blog https://sequencing.qcfail.com/articles/positional-sequence-bias-in-random-primed-libraries/
Thank you for the reply.
Based on further reading, I actually came across 2 articles that refer to this positional bias resulting from the insertion bias of the transposases used during tagmentation. Just sharing the references for anyone who had the same issue.
Article 1: https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0253440#pone.0253440.ref008
Article 2: https://pmc.ncbi.nlm.nih.gov/articles/PMC3292447/#abstract1