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We have been preparing libraries for Illumina GA and we have some problems with RNA-seq libraries. The issue that we are having is that we are seeing two peaks in bioanalyzer data (attached ppt). We are seeing this in all our RNA seq samples - no matter what organism used. We are using Illumina RNAseq kit. have anyone seen something like this? I would really appreciate any advice.
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I've seen this with ChIP-Seq libraries. I think the double peak is due to library PCR dimers forming. This is similar to primer-dimers but forms from PCR products dimerizing.
You see this more often if you use high cycle numbers in your amplification. -
This happens in about a third of my RNA-Seq library preps. Try using the ultrapure T4 ligase from Enzymatics and titrating the amount of primers in the final step, going down by 0.1ul amounts from 1ul.Comment
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two rounds DSN normalization
hello
has anyone tried to do two rounds of DSN normalization (specifically for RNA-seq)? If so, how did you do it and how did it go? Thanks.Comment
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I have done just one round of DSN normalization using Illumina's DSN normalization kit. The protocol of which can be found at http://qb3.berkeley.edu/gsl/Protocol...OT_RELEASE.pdfOriginally posted by zorph View PostComment
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We are also seeing double peaks in our RNA-seq library preps, even though all samples have been gel extracted at 350bp. Does anyone know how it is possible to still have 700 bp fragments after gel extraction and what we can do to remove the longer fragments? Thanks.Comment
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...06-18-2026, 07:11 AM -
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM
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