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  • Regions of extreme bias in histone modification runs

    Here at Univ of Penn we have been running histone modification experiments on solexa and as a control we run input sample that has not been immunoprecipitated. In the controls, as well as the samples, we see a significant number, maybe a hundred, of short regions where tons of reads pile up. In the samples we see the same effects in the same regions and we assume they are not real because they also happen in the control. These regions tend to be consistent from sample to sample and run to run. This is AFTER strong repeat masking so should have nothing to do with repeats.

    As a result we've had to run controls every time and remove those regions where this is happening. We are not sure if this is happening to everybody or if it's just us. Has anybody else had similar experience, or has anybody else gotten this to work without such artifacts? Any feedback is greatly appreciated, thank you.


  • #2
    Hi Greg,

    As far as I'm aware everyone finds these regions. They seem to hold across different samples as well, so they're definitely there.

    I believe the ChIP-Seq people here have compiled a list of these regions and just drop them from all ChIP-Seq results.

    Anthony
    The more you know, the more you know you don't know. —Aristotle

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    • #3
      Hi,

      In our ChIP-Seq experiments we also see something similar. Not sure why. But in our case they are strand dependent (they pile up in some short region but only mapping to one strand), so what we are doing is:
      1) Map reads depending of the strand
      2) Extend directionally the reads
      3) At each nucleotide position, count the number of reads that map in each strand, and take the minimum.

      So, these regions with reads mapping just in one strand are eliminated.

      Hope that it helps you,
      Jose

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      • #4
        That interesting, Cheema,

        I didn't know they were strand dependent. Thanks!

        Anthony
        The more you know, the more you know you don't know. —Aristotle

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        • #5
          Thanks everybody for your replies this is very useful we thought it was just us. I'm going to check if we have the same single strand problem and I'll let you all know, if that is happening to us that would be a nice way to filter for them. Thanks again!

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          • #6
            Strand specific artifacts?

            I checked on the strand specific thing and unfortunately it is not happening in our data. Has anybody else seen the strand specific thing happening?

            Somebody mentioned that illumina might have a master list of problematic regions, can anybody point me to where I might obtain that list?

            Thanks again everybody for your replies this has been extremely helpful!

            Greg

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            • #7
              I wonder if some of these 'consistent false peak' sites may be due to preferential shearing of DNA at active polII sites:

              Looking at the data in the Rozowsky 2008 paper (PeakSeq enables sytematic scoring of ChIP-seq experiments relative to controls) it appears that ChIP polII peaks correlate very well with peaks in the anti-body free input DNA controls. The paper address this to some degree. Additionally, work that I read somewhere about tethering of DNA in the nucleus showed that DNA appears to tethered to the nuclear cage by active transcription units. I wonder if this may lead to preferential presence of tags in ChIP-seq datasets because of preferential shearing of genomic DNA at the tethered sites, during the DNA extraction process, or perhaps due to some other reason.

              Either way, part of the answer would be to include a polII ChIP dataset as part of the control, and to have an peak calling algorythm which adjusted for the active polII sites under the relavant conditions...resources permitting.


              Mike F.
              SBL UK

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              • #8
                Greg,

                What size range of DNA do you create before immunoprecipitaion, and what size range do you then sub-select for illumina libary preparation?

                Mike

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                • #9
                  what happens if you eliminate all non-unique reads from your analysis?

                  i usually obtain rather 'flat' inputs if i remove the non-unique reads and, of course, the ones that map multiple locations

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