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  • michaelsbrewer
    Junior Member
    • Jul 2012
    • 2

    #1

    Trinity assemblies do not contain isoforms?!

    I recently assembled a number of transcriptomes using the Trinity pipeline. All proceeded smoothly until I began looking for isoforms. Most of the assemblies do not have any while a few have only a hand full (~5). All of the comp#s end in "_c0_seq1". My sequencing was not terribly deep; we multiplexed four individuals per lane of an illumina flow cell for RNAseq. Perhaps the sequencing was not deep enough to recover many isoforms?

    I guess what I am asking is, how many isoforms should one expect from a Trinity assembly (e.g., 22,623 sequences in the Trinity.fasta output; average length of 610 nucleotides) sequenced in such a manner?

    Thanks,
    Michael
  • Jeremy
    Senior Member
    • Nov 2009
    • 190

    #2
    Number of isoforms depends on your sample, for example bacteria would not have many whereas a human would have more. Also, is it paired end data or single end, paired end data has more information that can be used to identify isoforms than single end.

    Comment

    • michaelsbrewer
      Junior Member
      • Jul 2012
      • 2

      #3
      Jeremy,

      The data were paired-end reads obtained from whole body extractions of arthropods (millipedes and spiders). Data concerning isoforms from these taxa are nearly non-existant as little work has been done in these organisms. Any advice or insight would be appreciated.

      Comment

      • Jeremy
        Senior Member
        • Nov 2009
        • 190

        #4
        I guess either there just aren't many alternately spliced genes in millipedes and spiders or Trinity doesn't perform well with these organisms. As with all NGS data, try a few other assembly programs and see how they look.

        Comment

        • Apexy
          Member
          • Apr 2011
          • 62

          #5
          Given that trinity is locked in a single k-mer could be another reason why you have few isoforms. You should be able get diverse rnatigs with lower k-mers. Like Jeremy mentioned, it depends also on your data (false k-mers introduced by sequencing errors). Trying out another assembler is good, and you should envisage how you will be able to filter novelty (genuine isoforms) vs noise (bogus isoforms).

          Comment

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