Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • RNA-seq: read counts in single- vs paired-end sequences

    Hi,

    I've read several threads with very related topics, but none have addressed the one simple question I have (which stems from my being new to this).

    We already have an assembled transcriptome (from 454 data), and would now like to do an experiment to assess differential gene expression with Illumina.

    My question is (assume one Illumina lane is being sequenced): will a 2 x 100 bp paired-end lane generate approximately HALF the number of reads of a 1 x 100 bp single end lane? (By read I mean a copy of a transcript, i.e. the two ends of a paired-end sequence count as only ONE read, for my purposes)

    I would assume so, since the sequencing effort (in terms of base pairs) for such a paired-end is twice that of the single end.

    Since I'm interested only in maximizing read counts, the extra information that comes in the paired-end sequence is not of interest to me at this point.

    Any insight regarding the comparison of read counts per sequencing effort between the two methods would be greatly appreciated.

    Thanks!

  • #2
    You produce the same number of reads. In a paired end run, you sequence BOTH ends of the same fragment, so both reads are coming from the same cluster on the flow cell. So with a paired-end run, you are getting exactly the same number, so this has no effect on your total read count (if you count the paired end reads as one read).

    The advantage of a paired end run is that you can align the reads with greater confidence.

    Comment


    • #3
      Thanks for insight! But wouldn't a a 2 x 100bp paired-end run be sequencing a total of 200bp from each sequence (i.e. transcript copy), 100bp from each end?

      So if a run sequences 1,000,000 bp (I know it's more, but just to keep it simple), I would get 5000 paired-end and 10,000 single end reads. Am I thinking about this wrong?

      Thanks again!

      Comment


      • #4
        I think you are confusing base pairs sequenced with reads count. The number of reads you get is a factor of the number of clusters on a flow cell. I think the recommended cluster density on an Illumina Hi-seq typically gives you ~65 millions per lane (somebody correct me if I am wrong). From these 65 million reads, doing a paired end sequencing run vs a single end run means that you will get 65 million pairs (or 130 million reads) vs 65 million single end reads. However, since you sequenced 200 bps versus 100 bps, you will get double the number of base pairs sequenced.

        If all you are doing is differential gene expression, then you are not really concerned with base pairs sequenced, just number of reads. In this, paired end versus single end doesn't affect the number of reads.

        Comment


        • #5
          That's great to know! Thanks a lot!
          My confusion was that, in my simple mind, the sequencing effort (in bp) versus number of reads had to balance out such that getting longer sequences would mean getting fewer. But if not, like you said, then paired-end seems like the way to go.

          Much appreciated!

          Comment

          Latest Articles

          Collapse

          • seqadmin
            Genetic Variation in Immunogenetics and Antibody Diversity
            by seqadmin



            The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben Martínez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...
            11-06-2024, 07:24 PM
          • seqadmin
            Choosing Between NGS and qPCR
            by seqadmin



            Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...
            10-18-2024, 07:11 AM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by seqadmin, Today, 11:09 AM
          0 responses
          23 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, Today, 06:13 AM
          0 responses
          20 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 11-01-2024, 06:09 AM
          0 responses
          30 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 10-30-2024, 05:31 AM
          0 responses
          21 views
          0 likes
          Last Post seqadmin  
          Working...
          X