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If it's daisy chaining/bubble product, you should be able to take a small amount, re-amplify it for a few cycles and the secondary peak will go away. As far as over-amplification goes- I usually use NEB and they give you a number of cycles based on your input. It's hard to tell if you've over-amplified or not based on the presence of bubble product alone. It's more of a relationship between the input DNA, the primer concentration, and the number of cycles you've done. Daisy chaining/Bubble product basically means that you have more cycles than primer.
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Jumping in to address my own question:
The fact that this pattern appears consistently indicates some systematic error/issue. Looking back at old gels, I noticed that some of my digests showed faint evidence of "banding" at lower molecular weights. What's more, the sizes of these bands are consistent across samples/digests.
My new hypothesis is that one of these undigested "bands" is overrepresented in my library, resulting in amplification bias.
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Is this library overamplification? Is this problematic?
Aloha all,
I definitely DO have library overamplification in some of my libraries (as evidenced by a secondary peak, likely the result of the "daisy-chaining" effect). But that's not really what has me curious.
I've attached an image below of the electropherogram of two of my libraries. What has my attention is the strong peak around 400 bp (~ 407 bp), and the small shoulder to the left (~ 380 bp), especially in D702. D709 has both peaks, but there is more "equal" representation of the sizes/fragments across the range. Libraries like D702 are in the majority.
After Pippin-Prep size selection, the elution was split into four separate PCRs, then pooled and cleaned. So this pattern has emerged independently not only across libraries, but presumably across independent PCRs within libraries, with remarkable consistency.
My question is: is this the result of overamplification (my original size-selection encompassed a range of ~ 70 bp, so it's tight), and could this reduce the complexity of my libraries? Or is this simply what I might expect to see given a relatively tight size-selection?
Side-note: I'm using such a tight size-range because my study organism has a 7-8 Gbp genome.
Last edited by Carcharodon; 09-27-2019, 02:02 PM.Tags: None
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