IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v14y2015i1p65-81n6.html
   My bibliography  Save this article

Inference for one-step beneficial mutations using next generation sequencing

Author

Listed:
  • Wojtowicz Andrzej J.
  • Miller Craig R.
  • Joyce Paul

Abstract

Experimental evolution is an important research method that allows for the study of evolutionary processes occurring in microorganisms. Here we present a novel approach to experimental evolution that is based on application of next generation sequencing. Under this approach population level sequencing is applied to an evolving population in which multiple first-step beneficial mutations occur concurrently. As a result, frequencies of multiple beneficial mutations are observed in each replicate of an experiment. For this new type of data we develop methods of statistical inference. In particular, we propose a method for imputing selection coefficients of first-step beneficial mutations. The imputed selection coefficient are then used for testing the distribution of first-step beneficial mutations and for estimation of mean selection coefficient. In the case when selection coefficients are uniformly distributed, collected data may also be used to estimate the total number of available first-step beneficial mutations.

Suggested Citation

  • Wojtowicz Andrzej J. & Miller Craig R. & Joyce Paul, 2015. "Inference for one-step beneficial mutations using next generation sequencing," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(1), pages 65-81, February.
    • Handle: RePEc:bpj:sagmbi:v:14:y:2015:i:1:p:65-81:n:6
    DOI: 10.1515/sagmb-2014-0030
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/sagmb-2014-0030
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/sagmb-2014-0030?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gregory I. Lang & Daniel P. Rice & Mark J. Hickman & Erica Sodergren & George M. Weinstock & David Botstein & Michael M. Desai, 2013. "Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations," Nature, Nature, vol. 500(7464), pages 571-574, August.
    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. Andreas Wagner, 2023. "Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Sébastien Boyer & Lucas Hérissant & Gavin Sherlock, 2021. "Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment," PLOS Genetics, Public Library of Science, vol. 17(1), pages 1-27, January.
    3. Andrea Fulgione & Célia Neto & Ahmed F. Elfarargi & Emmanuel Tergemina & Shifa Ansari & Mehmet Göktay & Herculano Dinis & Nina Döring & Pádraic J. Flood & Sofia Rodriguez-Pacheco & Nora Walden & Marcu, 2022. "Parallel reduction in flowering time from de novo mutations enable evolutionary rescue in colonizing lineages," Nature Communications, Nature, vol. 13(1), pages 1-14, 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:bpj:sagmbi:v:14:y:2015:i:1:p:65-81:n:6. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.