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  • adamreid
    Junior Member
    • Nov 2009
    • 6

    Problems with low input single-cell RNA-seq

    We are trying to sequence RNA from individual small cells.

    We are sorting by FACS and using SmartSeq2 and Nextera XT to make libraries.

    We have had several problems.

    We get rRNA contamination from both E. coli (perhaps due to contaminated reverse transcriptase) and from our target organism. This is strange because SmartSeq2 should only amplify polyA mRNAs.

    Secondly when we sequence the libraries we get adaptor contamination, sometimes from the strand-switching oligo and also from the Nextera transposase.

    Has anyone noticed similar problems?

    Cheers,

    Adam
  • nucacidhunter
    Jafar Jabbari
    • Jan 2013
    • 1250

    #2
    I would suggest you post in the following thread:

    Comment

    Latest Articles

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    • GATTACAT
      Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by GATTACAT
      Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
      07-01-2026, 11:43 AM
    • SEQadmin2
      Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by SEQadmin2


      I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

      Here are nine questions we think about, in roughly the order they matter, before...
      06-18-2026, 07:11 AM

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