IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v85y2013icp73-85.html
   My bibliography  Save this article

Modeling the effect of changing selective pressures on polymorphism and divergence

Author

Listed:
  • Benger, Etam
  • Sella, Guy

Abstract

The most common models of sequence evolution used to make inferences about adaptation rely on the assumption that selective pressures at a site remain constant through time. Instead, one might plausibly imagine that a change in the environment renders an allele beneficial and that when it fixes, the site is now constrained—until another change in the environment occurs that affects the selective pressures at that site. With this view in mind, we introduce a simple dynamic model for the evolution of coding regions, in which non-synonymous sites alternate between being fixed for the favored allele and being neutral with respect to other alleles. We use the pruning algorithm to derive closed forms for observable patterns of polymorphism and divergence in terms of the model parameters. Using our model, estimates of the fraction of beneficial substitutions α would remain similar to those obtained from existing approaches. In this framework, however, it becomes natural to ask how often adaptive substitutions originate from previously constrained or previously neutral sites, i.e., about the source of adaptive substitutions. We show that counts of coding sites that are both polymorphic in a sample from one species and divergent between two others carry information about this parameter. We also extend the basic model to include the effects of weakly deleterious mutations and discuss the importance of assumptions about the distribution of deleterious mutations among constrained non-synonymous sites. Finally, we derive a likelihood function for the parameters and apply it to a toy example, variation data for coding regions from chromosome 2 of the Drosophila melanogaster subgroup. This modeling work underscores how restrictive assumptions about adaptation have been to date, and how further work in this area will help to reveal unexplored and yet basic characteristics of adaptation.

Suggested Citation

  • Benger, Etam & Sella, Guy, 2013. "Modeling the effect of changing selective pressures on polymorphism and divergence," Theoretical Population Biology, Elsevier, vol. 85(C), pages 73-85.
  • Handle: RePEc:eee:thpobi:v:85:y:2013:i:c:p:73-85
    DOI: 10.1016/j.tpb.2012.10.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580912000962
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2012.10.001?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. Cathy Haag-Liautard & Mark Dorris & Xulio Maside & Steven Macaskill & Daniel L. Halligan & Brian Charlesworth & Peter D. Keightley, 2007. "Direct estimation of per nucleotide and genomic deleterious mutation rates in Drosophila," Nature, Nature, vol. 445(7123), pages 82-85, January.
    2. Carlos D. Bustamante & Rasmus Nielsen & Stanley A. Sawyer & Kenneth M. Olsen & Michael D. Purugganan & Daniel L. Hartl, 2002. "The cost of inbreeding in Arabidopsis," Nature, Nature, vol. 416(6880), pages 531-534, April.
    3. Justin C. Fay & Gerald J. Wyckoff & Chung-I Wu, 2002. "Testing the neutral theory of molecular evolution with genomic data from Drosophila," Nature, Nature, vol. 415(6875), pages 1024-1026, February.
    4. Nick G. C. Smith & Adam Eyre-Walker, 2002. "Adaptive protein evolution in Drosophila," Nature, Nature, vol. 415(6875), pages 1022-1024, February.
    5. Pleuni S Pennings & Joachim Hermisson, 2006. "Soft Sweeps III: The Signature of Positive Selection from Recurrent Mutation," PLOS Genetics, Public Library of Science, vol. 2(12), pages 1-15, 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. Sella, Guy, 2009. "An exact steady state solution of Fisher’s geometric model and other models," Theoretical Population Biology, Elsevier, vol. 75(1), pages 30-34.
    2. Kirsten E Eilertson & James G Booth & Carlos D Bustamante, 2012. "SnIPRE: Selection Inference Using a Poisson Random Effects Model," PLOS Computational Biology, Public Library of Science, vol. 8(12), pages 1-14, December.
    3. RoyChoudhury, Arindam & Wakeley, John, 2010. "Sufficiency of the number of segregating sites in the limit under finite-sites mutation," Theoretical Population Biology, Elsevier, vol. 78(2), pages 118-122.
    4. Amei Amei & Stanley Sawyer, 2012. "Statistical Inference of Selection and Divergence from a Time-Dependent Poisson Random Field Model," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-7, April.
    5. Toni I Gossmann & David Waxman & Adam Eyre-Walker, 2014. "Fluctuating Selection Models and Mcdonald-Kreitman Type Analyses," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-5, January.
    6. Michael DeGiorgio & Zachary A Szpiech, 2022. "A spatially aware likelihood test to detect sweeps from haplotype distributions," PLOS Genetics, Public Library of Science, vol. 18(4), pages 1-37, April.
    7. Juan M Calvo-Martín & Montserrat Papaceit & Carmen Segarra, 2017. "Molecular population genetics of the Polycomb genes in Drosophila subobscura," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-15, September.
    8. Garud, Nandita R. & Rosenberg, Noah A., 2015. "Enhancing the mathematical properties of new haplotype homozygosity statistics for the detection of selective sweeps," Theoretical Population Biology, Elsevier, vol. 102(C), pages 94-101.
    9. Yichen Zheng & Thomas Wiehe, 2019. "Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-32, November.
    10. Rouzine, Igor M. & Coffin, John M., 2010. "Multi-site adaptation in the presence of infrequent recombination," Theoretical Population Biology, Elsevier, vol. 77(3), pages 189-204.
    11. Rachel A Myers & Ferran Casals & Julie Gauthier & Fadi F Hamdan & Jon Keebler & Adam R Boyko & Carlos D Bustamante & Amelie M Piton & Dan Spiegelman & Edouard Henrion & Martine Zilversmit & Julie Huss, 2011. "A Population Genetic Approach to Mapping Neurological Disorder Genes Using Deep Resequencing," PLOS Genetics, Public Library of Science, vol. 7(2), pages 1-10, February.
    12. Xinkai Wu & Mengze Xu & Jian-Rong Yang & Jian Lu, 2024. "Genome-wide impact of codon usage bias on translation optimization in Drosophila melanogaster," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    13. Joo Hyun Im & Brian P Lazzaro, 2018. "Population genetic analysis of autophagy and phagocytosis genes in Drosophila melanogaster and D. simulans," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-17, October.
    14. Xinru Zhang & Bohao Fang & Yi-Fei Huang, 2023. "Transcription factor binding sites are frequently under accelerated evolution in primates," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    15. Smadi, Charline, 2015. "An eco-evolutionary approach of adaptation and recombination in a large population of varying size," Stochastic Processes and their Applications, Elsevier, vol. 125(5), pages 2054-2095.
    16. Junhui Peng & Li Zhao, 2024. "The origin and structural evolution of de novo genes in Drosophila," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    17. Vogl, Claus & Mikula, Lynette Caitlin, 2021. "A nearly-neutral biallelic Moran model with biased mutation and linear and quadratic selection," Theoretical Population Biology, Elsevier, vol. 139(C), pages 1-17.
    18. Hakhamanesh Mostafavi & Tomaz Berisa & Felix R Day & John R B Perry & Molly Przeworski & Joseph K Pickrell, 2017. "Identifying genetic variants that affect viability in large cohorts," PLOS Biology, Public Library of Science, vol. 15(9), pages 1-29, September.

    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:eee:thpobi:v:85:y:2013:i:c:p:73-85. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.