Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • ebeyne
    Junior Member
    • Apr 2010
    • 2

    454 vs. Solexa to improve sequence quality and depth

    Hello,

    we study the genetic polymorphism (at transcriptomic level) between two species.
    We are looking for some informations to improve our transcriptomic analysis.
    For the moment, we had sequenced the transcriptome of two insect species by an 454-titanium half-run.

    We would like to improve the sequence quality by either another 454 sequencing half-run either a Solexa sequencing (100bp, 15-20X coverage, more expensive)?

    So, is anyone in the same case (454 done then choice between 454 and Solexa)? What have you chosen? Are the results (better depth with 454 or complement methods 454+Solexa) as good as you hoped?
    Thanks for your help!
  • NextGenSeq
    Senior Member
    • Apr 2009
    • 482

    #2
    454 was the first to market and thus the oldest technology. It's also the most expensive.
    Illumina is the current market leader. I personally wouldn't even consider purchasing a 454 system.

    Comment

    • ECO
      --Site Admin--
      • Oct 2007
      • 1360

      #3
      Originally posted by NextGenSeq View Post
      454 was the first to market and thus the oldest technology. It's also the most expensive.
      Illumina is the current market leader. I personally wouldn't even consider purchasing a 454 system.
      Age of technology has nothing to do with utility of the reads. I think you're letting your crotchety-ness influence your posting.

      To the OP, at some point any read/mate length will saturate from an information perspective, where it saturates is going to depend on the characteristics of your genome and the read/mate lengths (and various other factors...seq methodology, library bias, etc). Given the same costs (and without knowing the size/repeat content of your genome, or if you have a reference already...) I would guess that mixing data types would get you to a more information-rich state.

      Comment

      • krobison
        Senior Member
        • Nov 2007
        • 734

        #4
        Different technologies have different dominant error modes; mixing techs should enable better data.

        Illumina will also allow much greater sampling depth, which would seem to be an overall win for any transcriptome project (lower expressed messages, more sampling of possible allele-specific effects, better precision in estimating expression level due to more counts). There are several papers in the cancer genomics field using mixture of 454 & Illumina with 454 providing scaffolding & Illumina piling on the read counts. IMO, the best summary of these can be found in a recent review.

        Comment

        • BaCh
          Member
          • May 2008
          • 81

          #5
          Originally posted by ebeyne View Post
          So, is anyone in the same case (454 done then choice between 454 and Solexa)? What have you chosen? Are the results (better depth with 454 or complement methods 454+Solexa) as good as you hoped?
          Not exactly the same case: I'm more or less regularly doing 454 genomes of bacteria. But perhaps it might help you when I say that nowadays I *always* add in a round of Solexa to get rid of frequent errors in 454 (homopolymers, base switches etc.).

          As I see it, neither of the technologies is superior to the other, they both have their strengths and weaknesses. Using both to cancel out the respective weaknesses has proven to be a very effective method for me. Just to give you an idea: my last benchmarks were: 2 errors in a 454/Solexa hybrid of a 4.something Mbp bacterium. I think that's not too bad.

          Originally posted by NextGenSeq View Post
          454 was the first to market and thus the oldest technology. It's also the most expensive.
          Illumina is the current market leader. I personally wouldn't even consider purchasing a 454 system.
          I first wanted to answer with the "wheel" being a first to market and ancient technology, but let's keep it with sequencing: Sanger sequencing is from the stone age of sequencing. Yet, if I could choose between a well made Sanger paired-library and a well made 454 or Solexa paired library ... for paired-end, almost everything but costs (and perhaps problem with certain sequences) let the Sanger library win hands down.

          Though I'm curious how PacBio might re-shuffle the deck there.

          B

          PS: But at least I learned a new expression: crotchety-ness. How lovely

          Comment

          • flxlex
            Moderator
            • Nov 2008
            • 412

            #6
            Originally posted by BaCh View Post
            Not exactly the same case: I'm more or less regularly doing 454 genomes of bacteria. But perhaps it might help you when I say that nowadays I *always* add in a round of Solexa to get rid of frequent errors in 454 (homopolymers, base switches etc.).
            Just out of curiosity, how do you do the actual error correcting, using what program/pipeline?

            Comment

            • BaCh
              Member
              • May 2008
              • 81

              #7
              Originally posted by flxlex View Post
              Just out of curiosity, how do you do the actual error correcting, using what program/pipeline?
              MIRA. Disclaimer: I'm the author of that beast, so I am probably not as impartial as I perhaps should.

              That being said ... the easiest approach is 454 de-novo (or 454 + Sanger hynrid de-novo), then map Solexa against the whole multiple alignment (not only the consensus). MIRA flags each position where 454 (or 454 + Sanger) and Solexa disagree. Using a good finishing editor (I use gap4) it doesn't take long to go through all positions.

              I would use 454 + Solexa hybrid de-novo only in the following cases:
              1) long Solexa paired-end library (3kb)
              or
              2) low coverage of 454. Then combined with Solexa pe-lib.

              Oh, and be wary of eventual GC bias in newer Solexa data. I have a data set of a bacterium (60%GC) with a few stretches at 45% and reads occurring there are ~3x more abundant than in the 60% areas. Same thing for a 45% bacterium with 35% areas. This breaks a lot of assumptions of de-novo assemblers.

              B.

              Comment

              • ebeyne
                Junior Member
                • Apr 2010
                • 2

                #8
                Hello,

                thank for all yours comments about my problem! I add some details about my data.

                Because of some technical problems, we must use the DNA library used to the 454 sequencing : it has the 454 adapters on both sides. So, to avoid to sequence only adapters, the company proposes us to concat the DNA library (5' and 3' joined) then to nebulaze the new fragment following a Illumina sequencing with the 100-pb kit (single-reads).

                Does anyone know if the presence of secondary/tertiary structures in DNA (due to many adapter sequences) could prevent the nebulization to be random?

                Comment

                Latest Articles

                Collapse

                • SEQadmin2
                  Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
                  by SEQadmin2



                  Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
                  ...
                  Yesterday, 11:10 AM
                • SEQadmin2
                  Cancer Drug Resistance: The Lingering Barrier to Rising Survival
                  by SEQadmin2



                  Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

                  There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
                  07-08-2026, 05:17 AM
                • 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

                ad_right_rmr

                Collapse

                News

                Collapse

                Topics Statistics Last Post
                Started by SEQadmin2, Yesterday, 10:04 AM
                0 responses
                11 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 07-08-2026, 10:08 AM
                0 responses
                9 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 07-07-2026, 11:05 AM
                0 responses
                17 views
                0 reactions
                Last Post SEQadmin2  
                Started by SEQadmin2, 07-02-2026, 11:08 AM
                0 responses
                31 views
                0 reactions
                Last Post SEQadmin2  
                Working...