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  • FastQC "Per Base Sequence Content": systematic deviation at 3' end of reads

    I have 101 bp Illumina GA IIx RNA-seq reads that display strange behavior in their FastQC "Per Base Sequence Content". I'm wondering if anyone knows what is causing this, or has seen similar behavior in their own data.

    The FastQC "Per Base Sequence Content" metric measures the proportion of G,T,A, and C content as a function of position along the read. For a random library, the %G, %T, %A, and %C lines should be roughly constant for all positions and should reflect the amount of these bases in the genome.

    In the case of my 101 bp reads, the %G, %A, %T, and %C are roughly constant through most of the cycles.... and then as the quality drops toward the 3' ends of the reads, the %G and %A systematically rise while %T and %C systematically drop.

    This occurs for both of the lanes we ran, and for both reads of the paired-end libraries. It does not occur, however, in the PhiX lane (but the PhiX lane had better quality).

    I attach the FastQC graph, and also the "Per base sequence quality" metric for comparison. (The odd behavior in the first 13 bases at the 5' end are (as far as I know) normal for a random primed RNA-seq library. See Hansen, Brenner & Dudoit (2010), "Biases in Illumina transcriptome sequencing caused by random hexamer priming", http://nar.oxfordjournals.org/conten.../e131.abstract .)

    Explanations for this odd behavior? Comments? Should I be trimming the 3' ends off where %G, %T, %A, and %C deviate from their constant values?

    Thanks for any help anyone can give! And thanks, too, to the FastQC developers for a very useful tool!
    Attached Files

  • #2
    d f,

    Yes, I have seen this behavior before and tracked down the cause. Your library has a significant fraction of inserts which are shorter than 101 nt. The sequencing is reading through the entire fragment and running into the Illumina adapter at the 3' end; the Illumina adapter happens to be fairly G rich. I have confirmed this by identifying the Illumina adapter sequence at the 3' ends of a significant fraction of reads whenever I see this skewing in the % called bases. We also had some paired end runs with similar patterns and mapping the read pairs confirmed that the insert sizes were shorter than expected and shorter than the read length.

    I should note that Agilent traces for these libraries did not reveal the presence of short fragments, but identification of the adapter sequence and the mapping data show the Agilent traces were not reliable.

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    • #3
      Thanks much, kmcarr, for the info and for the speedy reply!

      Out of curiosity, I took the final 32bp from each read, and ran them through FastQC. Indeed, the Overrepresented Sequences are Illumina adapters or PCR primers.

      As a first step in my transcriptome analysis, I will be using TopHat, which requires all reads to be of fixed length. Would you suggest trimming off the 3' ends of all the reads to the same fixed length? Or identifying the reads that have adapter/primer at their 3' ends and discarding them?

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      • #4
        Given the quality profile of your run I'd be tempted to trim the whole lot back by 40bp or so if you're worried about the primers causing a problem. Since you're mapping to an existing transcriptome I don't think you'll actually lose much information by doing that - you'll still have plenty of sequence left to map.

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        • #5
          Thanks for the advice!!!

          This is my first time working with Illumina data, and my first time doing RNA-seq, so any and all advice is helpful!
          Last edited by d f; 09-28-2010, 12:04 PM.

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