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  • naamasht
    Junior Member
    • May 2023
    • 3

    #1

    Non-responsive over clustering issue

    Hello,

    I'm sequencing 16S libraries (prepared and sequenced according to the EMP protocol) on MiSeq using a V2 kit. We used to load 12pM with 25% PhiX. I've used this protocol many times before and got good sequencing results (high yield, %PF and %>=Q30​).

    The last library I've tried to sequence resulted in low %PF and very poor R2 Q scores. It looked like an over clustering issue, so we tried decreasing the loading concentration and tried loading 8, 6 and 4pM. There was no change in the cluster density (all were around 1,000-1,100).

    I've tried using new sequencing primers, but nothing changed. The MiSeq is ok (it's been checked by a technician and other runs worked fine), and we also checked the library quality with Tapestation and it looks good.
    Illumina representatives said I should keep lowering the loading concentration and increase PhiX to 50%. This seems pointless, since we see no change in cluster density when we use 1/3 of the regular concentration.

    Can anyone think of a reason this is happening? I'm at a loss...

    Thanks!
  • Ben3
    Member
    • Sep 2022
    • 79

    #2
    naamasht it sounds like you've already checked everything. But when you said you tried using new sequencing primers, do you mean new primers (16S V4 amplification primers) to generate the amplicons you use for your libraries? That would be the first I would change along with the 515F forward and 806R reverse primer.

    My next question is how are you quantifying your libraries before you pool and load them? I've always found this to be one of the biggest sources of variation in my data. I've had all types of kits go bad and get inaccurate concentrations prior to loading. Another thing I would sometimes do is dilute my libraries in half and quantify using the same method as before and see if the concentration was still registering as half the original concentration.

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    • naamasht
      Junior Member
      • May 2023
      • 3

      #3
      Thanks for the response Ben3.

      I changed R1SP, R2SP and ISP, not the primers used for creating the libraries. That's the next thing I intend to do.
      Can you explain to me how degradation of these primers can affect the sequencing this way?

      I usually use Quant-it to quantify the samples before pooling them, and I use Qubit to determine the concentration of my clean pool. For this library, I also used qPCR (with a freshly made calibration curve). The qPCR concentration was half of the Qubit concentration, which is even weirder, since the effective concentration on the flow cell was even lower than what was loaded.

      Comment

      • Ben3
        Member
        • Sep 2022
        • 79

        #4
        Hey naamasht,

        Honestly, I don't know if it will make a difference because normally having problems with those primers causes the opposite problem, i.e., underloading due to amplification errors. I think it might still be good to change them just to be sure something else isn't at play here.

        Although in my opinion, a better starting point might be to check the reagents you use to quantify with. Have you changed them recently or made any modifications to your normal quantification method? I have also had weird results from qPCR where the concentrations didn't match the other methods, and sometimes I would just go by the qubit values instead. Mostly because it often worked better and was more consistent with certain applications we ran.

        Comment

        • Seqing_guidance
          Junior Member
          • Jun 2023
          • 2

          #5
          You might want to check your Phix concentration, since they seem to vary tube to tube. I also had similar issues trying to sequence fungal ITS and lowering the concentration and spiking Phix in at 50% did help. Have you done a Phix-only run on your machine? That can show potential issues if the Phix is causing the overclusting (which an illumina rep said is rare but can happen).

          Comment

          • angelas
            Junior Member
            • Feb 2013
            • 3

            #6
            Hi! Did you resolve this issue? I am having this exact problem right now. A 16S library that keeps overclustering even after reducing loading concentration from 9pM to 4pM. I have used this protocol many times without issue until now...

            Comment

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