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  • #16
    Hi chadn737, thanks for your reply - you raise an interesting point about the depth. We need to start with cell numbers in the millions because that's the number of human peripheral blood T cells one needs to generate enough RNA to be in Illumina's recommended range. On the HiSeq it looks like we can expect around 100 million reads per lane. With 10 barcodes per lane, we can expect 10 million reads per sample, which would be a coverage of 10x if we start with 1 million cells, but even less if we start with more material. Do you think this is a big problem with our system? I must admit I struggle to understand the significance of coverage in mRNA seq experiments....

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    • #17
      Hi eab,
      The Illumina TruSeq RNA kit is cheap and fast, but I think it is easy to get poor yields for some of the samples in one or two steps and not really notice it. After the final PCR amplification everything looks fine. But is it?

      On the other hand 10 million reads on 200 bp amplicons is only asking for 2 pg of DNA. If you are willing to blow your whole library in a single lane (mixed in with 9 other libraries) and every amplicon molecule produces a cluster.

      That may seem confusing and not very useful, but thinking about a library as a collection of individual amplicon molecules derived from the RNA you started with, rather than a 12 pM solution you load into a flowcell, seems more concrete to me.

      --
      Phillip

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      • #18
        Hi Phillip, I think I follow what you're saying up top - that having a peak on the bioanalyzer at the end of a multistep, high-throughput library prep does not prove that everything went ok at every step. Maybe that bioA peak should be 10x larger than it is, and you lost 90% of your material, and the losses were uneven, resulting in bias. So when two libraries that were supposed to be identical yield divergent sequence data, bias due to uneven losses during library prep is a potential cause. Is that what you're saying?

        I don't understand what you're driving at with the rest of your post, though. Are you advocating fewer PCR cycles/no PCR?

        Eli

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        • #19
          Hi eab,

          What I see as the RNA TruSeq's main problem is that it has no QC that happens prior to the amplification enrichment step. Specifically, the numbers of library molecules could drop below the number of reads generated. If that is the case the data set will be "bottomed out". (Lots of PCR duplicate reads.)

          The rest of my post was me taking the contrary position and saying that really it was not that likely your library molecule numbers would end up being that low prior to PCR because 10 million amplicons would be 2 pg of DNA.

          To take that another step, what would 2 pg of amplicons look like after 15 cycles of amplification? 2^15 ~= 32,000x. So it would look like 64 ng. I guess if you see less than 100 ng of amplified library for a sample you might begin to worry about your library being bottomed out.

          Of course you actually have the sequence data, so you can probably tell from it whether your issue results from a surfeit of PCR duplicates. (With some caveats...)

          --
          Phillip

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          • #20
            Hi Phillip, I think I get you now. Thanks for the clarification.

            Picking up on your point about the lack of QC built into TruSeq - do you think that a qPCR using flowcell primers (as in the Kapa library quant kit) would be useful if added just after purifying ligation reaction, before amplification enrichment? If I did that, how would I use the info? Would I just have to question the sequence data from any library that was surprisingly scant before amplification? If I wind up with only a small amount of library after amplification, doesn't that provide the same info?

            Thanks very much for your advice

            Eli

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            • #21
              Hi Eli,
              In principle it should be possible to skip amplification altogether if you do qPCR on the unamplified library.
              We got post-amplification yields in some cases that were less than pre-amplification. (These were DNA libraries.) Probably an issue with the ampure reaction clean-up. The libraries went on to produce plenty of sequence and none of them looked "bottomed out".
              This is all just stuff to be aware of, in my opinion. The Illumina protocol should be fine in many cases. Might even be worth using their spike in controls. I personally an not yet able to get over the horror of adding extraneous DNA during library construction. But that is just me...

              --
              Phillip

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