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  • mbhudson
    Junior Member
    • Aug 2015
    • 3

    #1

    Weird bioanalzyer data, what do you think it means?

    We have done NGS on RNA/microRNA from tissue samples before, but this is our first time attempting microRNA-SEQ on RNA from serum exosomes. We used the Qiagen serum exoRNeasy kit and saw basically all the samples look like this when they were run on the bioanalyzer with the Total RNA Pico Kit. Is it worth trying to create libraries from this?
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  • kerplunk412
    Senior Member
    • Jun 2012
    • 119

    #2
    For miRNA-seq they are probably fine, miRNA seems to be pretty resistant to degradation. That being said, you will probably end up with more non-miRNA reads than you would with a tissue sample. I say use as much of the RNA as you can and give it a shot.

    I have extracted RNA from plasma and it looks pretty much the same, and I have had mixed results with the library prep. There is a theory that most plasma RNA is contained within exosomes and that is why it is not quickly degraded, so it makes sense that my plasma samples look like your exosomes. I actually did RNA extraction from tissue culture exosomes way back in grad school (~2009), but I don't think I ever ran that on a Bioanalyzer.

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    • mbhudson
      Junior Member
      • Aug 2015
      • 3

      #3
      I have run isolated RNA from exosomes in tissue culture media before on the bioanalyzer and it looked a lot different. However, because of the large volume of culture media I isolated exosomes via ultracentrif, as opposed to this kit. I also ran miR-SEQ and found there are a lot of microRNAs that are highly expressed in exosomes and a lot that are barely (if at all) present exosomes compared to tissue. Other studies have shown the same in serum exosomes.

      The Qiagen tech support claims this looks completely normal, and not to worry about it. ...I guess we'll see what happens.

      Looking at the TruSeq small RNA library kit it says it can use 10-50ng of purified small RNAs, which to me is what this bioanalzyer data looks like. So i guess i'll give it a shot.

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