IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v100y2015icp88-97.html
   My bibliography  Save this article

Covariation of gene frequencies in a stepping-stone lattice of populations

Author

Listed:
  • Felsenstein, Joseph

Abstract

For a one- or two-dimensional lattice of finite length consisting of populations, each of which has the same population size, the classical stepping-stone model has been used to approximate the patterns of variation at neutral loci in geographic regions. In the pioneering papers by Maruyama (1970a, 1970b, 1971) the changes of gene frequency at a locus subject to neutral mutation between two alleles, migration, and random genetic drift were modeled by a vector autoregression model. Maruyama was able to use the spectrum of the migration matrix, but to do this he had to introduce approximations in which there was either extra mutation in the terminal populations, or extra migration from the subterminal population into the terminal population. In this paper a similar vector autoregression model is used, but it proves possible to obtain the eigenvalues and eigenvectors of the migration matrix without those approximations. Approximate formulas for the variances and covariances of gene frequencies in different populations are obtained, and checked by numerical iteration of the exact covariances of the vector autoregression model.

Suggested Citation

  • Felsenstein, Joseph, 2015. "Covariation of gene frequencies in a stepping-stone lattice of populations," Theoretical Population Biology, Elsevier, vol. 100(C), pages 88-97.
  • Handle: RePEc:eee:thpobi:v:100:y:2015:i:c:p:88-97
    DOI: 10.1016/j.tpb.2014.12.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580914001002
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2014.12.004?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. Nick Patterson & Alkes L Price & David Reich, 2006. "Population Structure and Eigenanalysis," PLOS Genetics, Public Library of Science, vol. 2(12), pages 1-20, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Duforet-Frebourg, Nicolas & Slatkin, Montgomery, 2016. "Isolation-by-distance-and-time in a stepping-stone model," Theoretical Population Biology, Elsevier, vol. 108(C), pages 24-35.

    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. Gyaneshwer Chaubey & Anurag Kadian & Saroj Bala & Vadlamudi Raghavendra Rao, 2015. "Genetic Affinity of the Bhil, Kol and Gond Mentioned in Epic Ramayana," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-11, June.
    2. Daniel Svensson & Matilda Rentoft & Anna M Dahlin & Emma Lundholm & Pall I Olason & Andreas Sjödin & Carin Nylander & Beatrice S Melin & Johan Trygg & Erik Johansson, 2020. "A whole-genome sequenced control population in northern Sweden reveals subregional genetic differences," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-18, September.
    3. Estavoyer, Maxime & François, Olivier, 2022. "Theoretical analysis of principal components in an umbrella model of intraspecific evolution," Theoretical Population Biology, Elsevier, vol. 148(C), pages 11-21.
    4. Yaron Granot & Omri Tal & Saharon Rosset & Karl Skorecki, 2016. "On the Apportionment of Population Structure," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-24, August.
    5. Hyosik Jang & Ian M Ehrenreich, 2012. "Genome-Wide Characterization of Genetic Variation in the Unicellular, Green Alga Chlamydomonas reinhardtii," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    6. Mathieu Gautier & Denis Laloë & Katayoun Moazami-Goudarzi, 2010. "Insights into the Genetic History of French Cattle from Dense SNP Data on 47 Worldwide Breeds," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-11, September.
    7. Xiaofeng Cai & Xuepeng Sun & Chenxi Xu & Honghe Sun & Xiaoli Wang & Chenhui Ge & Zhonghua Zhang & Quanxi Wang & Zhangjun Fei & Chen Jiao & Quanhua Wang, 2021. "Genomic analyses provide insights into spinach domestication and the genetic basis of agronomic traits," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    8. Lee, Anthony J. & Hibbs, Courtney & Wright, Margaret J. & Martin, Nicholas G. & Keller, Matthew C. & Zietsch, Brendan P., 2017. "Assessing the accuracy of perceptions of intelligence based on heritable facial features," Intelligence, Elsevier, vol. 64(C), pages 1-8.
    9. Thompson Katherine L. & Linnen Catherine R. & Kubatko Laura, 2016. "Tree-based quantitative trait mapping in the presence of external covariates," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(6), pages 473-490, December.
    10. Matthieu Bouaziz & Caroline Paccard & Mickael Guedj & Christophe Ambroise, 2012. "SHIPS: Spectral Hierarchical Clustering for the Inference of Population Structure in Genetic Studies," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-17, October.
    11. Jacobo Pardo-Seco & Alberto Gómez-Carballa & Jorge Amigo & Federico Martinón-Torres & Antonio Salas, 2014. "A Genome-Wide Study of Modern-Day Tuscans: Revisiting Herodotus's Theory on the Origin of the Etruscans," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-11, September.
    12. Andrey V Khrunin & Denis V Khokhrin & Irina N Filippova & Tõnu Esko & Mari Nelis & Natalia A Bebyakova & Natalia L Bolotova & Janis Klovins & Liene Nikitina-Zake & Karola Rehnström & Samuli Ripatti & , 2013. "A Genome-Wide Analysis of Populations from European Russia Reveals a New Pole of Genetic Diversity in Northern Europe," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-9, March.
    13. Ilja M Nolte & Chris Wallace & Stephen J Newhouse & Daryl Waggott & Jingyuan Fu & Nicole Soranzo & Rhian Gwilliam & Panos Deloukas & Irina Savelieva & Dongling Zheng & Chrysoula Dalageorgou & Martin F, 2009. "Common Genetic Variation Near the Phospholamban Gene Is Associated with Cardiac Repolarisation: Meta-Analysis of Three Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 4(7), pages 1-10, July.
    14. Hoicheong Siu & Li Jin & Momiao Xiong, 2012. "Manifold Learning for Human Population Structure Studies," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-18, January.
    15. Elodie Persyn & Richard Redon & Lise Bellanger & Christian Dina, 2018. "The impact of a fine-scale population stratification on rare variant association test results," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    16. Andre Krumel Portella & Afroditi Papantoni & Catherine Paquet & Spencer Moore & Keri Shiels Rosch & Stewart Mostofsky & Richard S Lee & Kimberly R Smith & Robert Levitan & Patricia Pelufo Silveira & S, 2020. "Predicted DRD4 prefrontal gene expression moderates snack intake and stress perception in response to the environment in adolescents," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-20, June.
    17. Lindsay Fernández-Rhodes & Jennifer R Malinowski & Yujie Wang & Ran Tao & Nathan Pankratz & Janina M Jeff & Sachiko Yoneyama & Cara L Carty & V Wendy Setiawan & Loic Le Marchand & Christopher Haiman &, 2018. "The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic ," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-21, July.
    18. Pierre Luisi & Angelina García & Juan Manuel Berros & Josefina M B Motti & Darío A Demarchi & Emma Alfaro & Eliana Aquilano & Carina Argüelles & Sergio Avena & Graciela Bailliet & Julieta Beltramo & C, 2020. "Fine-scale genomic analyses of admixed individuals reveal unrecognized genetic ancestry components in Argentina," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-30, July.
    19. Peña-Malavera Andrea & Bruno Cecilia & Balzarini Monica & Fernandez Elmer, 2014. "Comparison of algorithms to infer genetic population structure from unlinked molecular markers," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(4), pages 1-12, August.
    20. Edoardo Saccenti & Marieke E. Timmerman, 2017. "Considering Horn’s Parallel Analysis from a Random Matrix Theory Point of View," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 186-209, March.

    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:100:y:2015:i:c:p:88-97. 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.