IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-29500-4.html
   My bibliography  Save this article

Designing highly multiplex PCR primer sets with Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE)

Author

Listed:
  • Nina G. Xie

    (Rice University)

  • Michael X. Wang

    (Rice University)

  • Ping Song

    (Rice University)

  • Shiqi Mao

    (Shanghai Pulmonary Hospital, Tongji University School of Medicine)

  • Yifan Wang

    (NuProbe China)

  • Yuxia Yang

    (NuProbe China)

  • Junfeng Luo

    (NuProbe China)

  • Shengxiang Ren

    (Shanghai Pulmonary Hospital, Tongji University School of Medicine)

  • David Yu Zhang

    (NuProbe USA)

Abstract

One major challenge in the design of highly multiplexed PCR primer sets is the large number of potential primer dimer species that grows quadratically with the number of primers to be designed. Simultaneously, there are exponentially many choices for multiplex primer sequence selection, resulting in systematic evaluation approaches being computationally intractable. Here, we present and experimentally validate Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE), a stochastic algorithm for design of multiplex PCR primer sets that minimize primer dimer formation. In a 96-plex PCR primer set (192 primers), the fraction of primer dimers decreases from 90.7% in a naively designed primer set to 4.9% in our optimized primer set. Even when scaling to 384-plex (768 primers), the optimized primer set maintains low dimer fraction. In addition to NGS, SADDLE-designed primer sets can also be used in qPCR settings to allow highly multiplexed detection of gene fusions in cDNA, with a single-tube assay comprising 60 primers detecting 56 distinct gene fusions recurrently observed in lung cancer.

Suggested Citation

  • Nina G. Xie & Michael X. Wang & Ping Song & Shiqi Mao & Yifan Wang & Yuxia Yang & Junfeng Luo & Shengxiang Ren & David Yu Zhang, 2022. "Designing highly multiplex PCR primer sets with Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE)," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29500-4
    DOI: 10.1038/s41467-022-29500-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-29500-4
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-29500-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Erin E. Heyer & Ira W. Deveson & Danson Wooi & Christina I. Selinger & Ruth J. Lyons & Vanessa M. Hayes & Sandra A. O’Toole & Mandy L. Ballinger & Devinder Gill & David M. Thomas & Tim R. Mercer & Jam, 2019. "Diagnosis of fusion genes using targeted RNA sequencing," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Feng Wang & Yang Xu & Robert Wang & Beatrice Zhang & Noah Smith & Amber Notaro & Samantha Gaerlan & Eric Kutschera & Kathryn E. Kadash-Edmondson & Yi Xing & Lan Lin, 2023. "TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29500-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.