trimming BGI adapters

[jgroh]

Hello,

I have paired-end 100bp reads generated from BGI-seq 500. The sequencing center did some adapter removal trimming before delivering the data but there appears to be a fraction of reads which still have putative adapter sequences. I am making this judgement based on the presence of 'overrepresented kmers' at the start and ends of both forward and reverse reads seen in the output of FastQC. I've included an image of this module output for one particular sample as an attachment.

The overrepresented kmer at the 3' end match the beginning of the 3' adapter sequence, which makes sense, and I assume this is due to cases where the insert size is less than the read length, so the reads sequence into the adapter on the other side of the genomic fragment.

What is confusing me is that the overrepresented kmers at the 5' end of reads contain what looks like partial sequence of the 5' adapter sequence, but degraded at the 3' end, which I wouldn't expect, and also with one base pair position variable. I wouldn't necessarily expect sequencing error either as the quality scores are generally very high at the start of the reads.

Here is the 5' adapter sequence provide by the sequencing center:
5' adapter AAGTCGGATCGTAGCCATGTCGTTCTGTGAGCCAAGGAGTTG. The underlined part is what is appearing in fragments at the start of reads, and the position in bold is variable among these. Libraries were prepared by the sequencing center, and the sequencing technology is still a bit unclear to me, so I'm not sure whether this is a true artefact. Has anyone seen this patterns in the data from BGI before? I may just leave the data as is and proceed with mapping, as these reads are a small fraction overall, but I'm trying to understand what might be going on....

Thanks

[Rnasoup]

Probably is a bit late for you, but I hope this may help other people. I struggled to find out the sequences to trim adapters from BGI/MGI sequencing data. At the end, I found a pdf with the oligos used for library prep

Normally I use grep to inspect the adapters, but with BGI/MGI it was confusing because I found that there are often mutations in the adapters (I rarely see it when looking Illumina data).

In short, for paired-end, this cutadapt command found adapters in around 10% of the read pairs in this dataset.

cutadapt -a AAGTCGGAGGCCAAGCGGTCTTAGGAAGACAA -A AAGTCGGATCGTAGCCATGTCGTTCTGTGAGCCAAGGAGTTG

[Melissa]

Hi,

Thanks Rnasoup for sharing the link to the sequencing adapter. I tried to find it but nothing showed up in google.

I hope jgroh resolved the adapter issue. It does look quite strange.

By the way, how do you find the data quality of MGI sequencer in terms of error rate etc?

Thanks
Melissa

[Rnasoup]

Thanks Melissa,

I am not sure which data quality you mean. Anyway, I don´t have much experience with MGI sequencing, I have just had to dig into it to analyze the GEO dataset that I mentioned in my post, so all I had was the fastq raw data. I guess you can run any software to extract quality information from the fastq files, like Picard tools.

Good luck

[Melissa]

Hi Rnasoup,

Thanks for your reply. What I meant is the data quality in terms of reported phred score vs observed phred score, substitution/indel error rate, problematic region for variant calling etc. Some metrics similar to this thread on a new sequencer.

Cheers
Melissa

[uzi_maruzi]

Probably is a bit late for you, but I hope this may help other people. I struggled to find out the sequences to trim adapters from BGI/MGI sequencing data. At the end, I found a pdf with the oligos used for library prep

Normally I use grep to inspect the adapters, but with BGI/MGI it was confusing because I found that there are often mutations in the adapters (I rarely see it when looking Illumina data).

In short, for paired-end, this cutadapt command found adapters in around 10% of the read pairs in this dataset.

cutadapt -a AAGTCGGAGGCCAAGCGGTCTTAGGAAGACAA -A AAGTCGGATCGTAGCCATGTCGTTCTGTGAGCCAAGGAGTTG

Thank you for sharing the adapters sequence. May I ask you if this adapters work for PE or just for SE? I am a bit confused in starting off my data analysis. the sequencing company provide me with the following adapters index:

		i7_Index_ID	i7index配列	i5_Index_ID	i5index配列
DNA	Index	i7ID	i7Seq	i5ID	i5Seq
SG-003	M5041/M7091	M7091	CAATCGTT	M5041	CTGCGGAT
SG-015	M5041/M7092	M7092	AGCCATAC	M5041	CTGCGGAT

....etc....

So, I used those sequence as adapter trimming. Am I wrong?

[TGRANGE]

Yes, you are wrong, these are the index sequences, they are in the middle of the adapter. You should use the sequences described by Rnasoup that are abutting the inserts and that should be used for trimming.

[uzi_maruzi]

Thank you TGRANGE!