Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Using multiple MIDs in titanium sequence runs

    Hi!

    So far I usually pool up to 5 MID-tagged libraries (genomic shotgun) per physically seperated region on a picotiterplate. Thus far this has resulted in up to 4-fold difference in traces per MID (eg: 30 Mb sequenced from 1 MID, 120 MB sequenced from another, where the targeted amount was 75 Mb). These libraries are equal in size distribution.

    Have any of you similar experiences and/or suggestions to level the amount of traces per MID, so the amount of sequence data is more equally distributed between MID libraries?

    Has someone tried combining 10+ MID tagged libraries in 1 region?

    Jurgen

  • #2
    Hi
    We regularly use up to 10 "in-house MIDs" for 454, and yes, balancing the load is very difficult. We regularly see 4-fold differences, often more. More accurate quantification might help, but I find it hard to believe that that is the only explanation. The emPCR probably introduces some bias as well. I was told by a pro that separate emPCRs for each MID might help.

    Comment


    • #3
      We have also done up to 10 MIDs and too have found wide variations in representation. We are currently quantitating using the Qubit fluorimeter but are considering qPCR.

      Originally posted by sulfobus View Post
      I was told by a pro that separate emPCRs for each MID might help.
      Not to be a negative Nancy but doesn't that defeat one of the most useful bits of using MIDs? The lab staff has to run only a single, large emPCR.

      Comment


      • #4
        Originally posted by kmcarr View Post
        Not to be a negative Nancy but doesn't that defeat one of the most useful bits of using MIDs? The lab staff has to run only a single, large emPCR.
        Indeed, but it saves some money in reagents and plates. The samples we sequence sometimes only contain ~1000 unique sequences, so even a 16th plate would be oversampling. That's why we use ID-tags and pool them.

        Comment


        • #5
          So far I have done some tweaking regarding this "problem". I think factors that influence the askew distribution in MID's are:

          1. Concentration of the stock DNA used right before pipetting into the emulsion PCR.
          2. Storage of the DNA: both temperature (libraries are single stranded and the DNA strands could form hydrogenbonds when stored to long at 4 degrees or kept too long on the bench at room temperature, both resulting in a reduction of single DNA copies that could end up in a micelle) and type of tubes (maybe an absolute number of DNA could stick to regular Eppendorf tubes - posing problems when storing too long resulting in a lower concentration than expected)

          I don't know about the influence of the emPCR: the reagents here are the same for all MID-tagged libraries, and the libraries are similar as well.

          Just some thoughts... Any other suggestions that contribute to this fenomenon?
          Last edited by JurgenP; 01-11-2010, 06:33 AM.

          Comment


          • #6
            Originally posted by JurgenP View Post
            Hi!

            So far I usually pool up to 5 MID-tagged libraries (genomic shotgun) per physically seperated region on a picotiterplate. Thus far this has resulted in up to 4-fold difference in traces per MID (eg: 30 Mb sequenced from 1 MID, 120 MB sequenced from another, where the targeted amount was 75 Mb). These libraries are equal in size distribution.

            Have any of you similar experiences and/or suggestions to level the amount of traces per MID, so the amount of sequence data is more equally distributed between MID libraries?

            Has someone tried combining 10+ MID tagged libraries in 1 region?

            Jurgen
            Yes, we used 10 MIDs in a single region. We also saw 4-fold differences--anywhere from 6.2 to 23 megabases of sequence for a sample. We did qPCR on each library prior to emPCR.

            These were SMART cDNA libraries. Could be the new rapid library technology would produce less varied amounts of sequence.

            That said, we were pretty happy with these results. And it was for 10 libraries, so seeing one or two outliers was not unexpected.

            --
            Phillip

            Comment


            • #7
              To add to Jurgen comments about DNA sticking to tubes-- most standard PP tubes bind DNA and other molecules. You should be able to find DNA/RNA lobind tubes in the market

              Originally posted by JurgenP View Post
              So far I have done some tweaking regarding this "problem". I think factors that influence the askew distribution in MID's are:

              1. Concentration of the stock DNA used right before pipetting into the emulsion PCR.
              2. Storage of the DNA: both temperature (libraries are single stranded and the DNA strands could form hydrogenbonds when stored to long at 4 degrees or kept too long on the bench at room temperature, both resulting in a reduction of single DNA copies that could end up in a micelle) and type of tubes (maybe an absolute number of DNA could stick to regular Eppendorf tubes - posing problems when storing too long resulting in a lower concentration than expected)

              I don't know about the influence of the emPCR: the reagents here are the same for all MID-tagged libraries, and the libraries are similar as well.

              Just some thoughts... Any other suggestions that contribute to this fenomenon?

              Comment


              • #8
                We have 132 in-house developed Titanium MIDs available for use. I think that the greatest number we have ever pooled in a single region for project data is somewhere around 110. Generally, our projects consist of pools of around 50-75 MID-tagged libraries.

                We have definitely noticed that quantitation makes a huge difference. What we'll generally do if we have a large range of concentrations (greater than 2-3 orders of magnitude) is that we'll make two pools--one of "high" concentration libraries and one of "low" concentration libraries. This can help to decrease any bias that we might see in the samples.

                Comment


                • #9
                  I have run 9 genomic libraries prepared with the Nextera kit in one region and saw max 2-fold diffs in yield. These were all pooled prior to emPCR. There was a weak relationship between library concentration as measured with picogreen and total read yield (R-squared 0.1). However, the libraries with the lowest read count were also those for which Bioanalyzer (DNA 7500) and picogreen (PG) quantitation were the most different. For most libs PG and Bioanalyzer agreed well but for the low yield libs there was a 30% difference. In fact, R-squared is 0.75 for the relationship between the ratio (PG conc/Bioanalyzer conc) to read yield (see attached). This suggests to me some inherent property of a few libraries that resulted in inaccurate quantitation with two different methods prior to the emPCR. In the future I'd probably apply both quantitation methods to the libraries, and for those with ratios < 0.8, up the amount of input DNA by ~50% to compensate.

                  Originally posted by pmiguel View Post
                  Yes, we used 10 MIDs in a single region. We also saw 4-fold differences--anywhere from 6.2 to 23 megabases of sequence for a sample. We did qPCR on each library prior to emPCR.

                  These were SMART cDNA libraries. Could be the new rapid library technology would produce less varied amounts of sequence.

                  That said, we were pretty happy with these results. And it was for 10 libraries, so seeing one or two outliers was not unexpected.

                  --
                  Phillip
                  Attached Files

                  Comment

                  Latest Articles

                  Collapse

                  • seqadmin
                    Best Practices for Single-Cell Sequencing Analysis
                    by seqadmin



                    While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
                    06-06-2024, 07:15 AM
                  • seqadmin
                    Latest Developments in Precision Medicine
                    by seqadmin



                    Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

                    Somatic Genomics
                    “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
                    05-24-2024, 01:16 PM

                  ad_right_rmr

                  Collapse

                  News

                  Collapse

                  Topics Statistics Last Post
                  Started by seqadmin, Today, 08:58 AM
                  0 responses
                  8 views
                  0 likes
                  Last Post seqadmin  
                  Started by seqadmin, Yesterday, 02:20 PM
                  0 responses
                  14 views
                  0 likes
                  Last Post seqadmin  
                  Started by seqadmin, 06-07-2024, 06:58 AM
                  0 responses
                  181 views
                  0 likes
                  Last Post seqadmin  
                  Started by seqadmin, 06-06-2024, 08:18 AM
                  0 responses
                  231 views
                  0 likes
                  Last Post seqadmin  
                  Working...
                  X