IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v108y2016icp24-35.html
   My bibliography  Save this article

Isolation-by-distance-and-time in a stepping-stone model

Author

Listed:
  • Duforet-Frebourg, Nicolas
  • Slatkin, Montgomery

Abstract

With the great advances in ancient DNA extraction, genetic data are now obtained from geographically separated individuals from both present and past. However, population genetics theory about the joint effect of space and time has not been thoroughly studied. Based on the classical stepping-stone model, we develop the theory of Isolation by distance and time. We derive the correlation of allele frequencies between demes in the case where ancient samples are present, and investigate the impact of edge effects with forward-in-time simulations. We also derive results about coalescent times in circular and toroidal models. As one of the most common ways to investigate population structure is principal components analysis (PCA), we evaluate the impact of our theory on PCA plots. Our results demonstrate that time between samples is an important factor. Ancient samples tend to be drawn to the center of a PCA plot.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:thpobi:v:108:y:2016:i:c:p:24-35
    DOI: 10.1016/j.tpb.2015.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580915001124
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2015.11.003?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. Barbara E Engelhardt & Matthew Stephens, 2010. "Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis," PLOS Genetics, Public Library of Science, vol. 6(9), pages 1-12, September.
    2. 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.
    3. John Novembre & Toby Johnson & Katarzyna Bryc & Zoltán Kutalik & Adam R. Boyko & Adam Auton & Amit Indap & Karen S. King & Sven Bergmann & Matthew R. Nelson & Matthew Stephens & Carlos D. Bustamante, 2008. "Genes mirror geography within Europe," Nature, Nature, vol. 456(7219), pages 274-274, November.
    4. Gil McVean, 2009. "A Genealogical Interpretation of Principal Components Analysis," PLOS Genetics, Public Library of Science, vol. 5(10), pages 1-10, October.
    5. Felsenstein, Joseph, 2015. "Covariation of gene frequencies in a stepping-stone lattice of populations," Theoretical Population Biology, Elsevier, vol. 100(C), pages 88-97.
    6. John Novembre & Toby Johnson & Katarzyna Bryc & Zoltán Kutalik & Adam R. Boyko & Adam Auton & Amit Indap & Karen S. King & Sven Bergmann & Matthew R. Nelson & Matthew Stephens & Carlos D. Bustamante, 2008. "Genes mirror geography within Europe," Nature, Nature, vol. 456(7218), pages 98-101, November.
    7. Frantz Depaulis & Ludovic Orlando & Catherine Hänni, 2009. "Using Classical Population Genetics Tools with Heterochroneous Data: Time Matters!," PLOS ONE, Public Library of Science, vol. 4(5), pages 1-16, May.
    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. 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.

    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. Bryc, Katarzyna & Bryc, Wlodek & Silverstein, Jack W., 2013. "Separation of the largest eigenvalues in eigenanalysis of genotype data from discrete subpopulations," Theoretical Population Biology, Elsevier, vol. 89(C), pages 34-43.
    2. Zheng, Xiuwen & Weir, Bruce S., 2016. "Eigenanalysis of SNP data with an identity by descent interpretation," Theoretical Population Biology, Elsevier, vol. 107(C), pages 65-76.
    3. Priya Moorjani & Nick Patterson & Joel N Hirschhorn & Alon Keinan & Li Hao & Gil Atzmon & Edward Burns & Harry Ostrer & Alkes L Price & David Reich, 2011. "The History of African Gene Flow into Southern Europeans, Levantines, and Jews," PLOS Genetics, Public Library of Science, vol. 7(4), pages 1-13, April.
    4. Wang Chaolong & Szpiech Zachary A & Degnan James H & Jakobsson Mattias & Pemberton Trevor J & Hardy John A & Singleton Andrew B & Rosenberg Noah A, 2010. "Comparing Spatial Maps of Human Population-Genetic Variation Using Procrustes Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-22, January.
    5. Aman Agrawal & Alec M Chiu & Minh Le & Eran Halperin & Sriram Sankararaman, 2020. "Scalable probabilistic PCA for large-scale genetic variation data," PLOS Genetics, Public Library of Science, vol. 16(5), pages 1-19, May.
    6. Jason Sawler & Bruce Reisch & Mallikarjuna K Aradhya & Bernard Prins & Gan-Yuan Zhong & Heidi Schwaninger & Charles Simon & Edward Buckler & Sean Myles, 2013. "Genomics Assisted Ancestry Deconvolution in Grape," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
    7. 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.
    8. 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.
    9. 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.
    10. Gad Abraham & Michael Inouye, 2014. "Fast Principal Component Analysis of Large-Scale Genome-Wide Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-5, April.
    11. Diana Chang & Alon Keinan, 2014. "Principal Component Analysis Characterizes Shared Pathogenetics from Genome-Wide Association Studies," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-14, September.
    12. Oscar Lao & Fan Liu & Andreas Wollstein & Manfred Kayser, 2014. "GAGA: A New Algorithm for Genomic Inference of Geographic Ancestry Reveals Fine Level Population Substructure in Europeans," PLOS Computational Biology, Public Library of Science, vol. 10(2), pages 1-11, February.
    13. Gil McVean, 2009. "A Genealogical Interpretation of Principal Components Analysis," PLOS Genetics, Public Library of Science, vol. 5(10), pages 1-10, October.
    14. Guindon, Stéphane & Guo, Hongbin & Welch, David, 2016. "Demographic inference under the coalescent in a spatial continuum," Theoretical Population Biology, Elsevier, vol. 111(C), pages 43-50.
    15. Marie-Claude Babron & Marie de Tayrac & Douglas N Rutledge & Eleftheria Zeggini & Emmanuelle Génin, 2012. "Rare and Low Frequency Variant Stratification in the UK Population: Description and Impact on Association Tests," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-9, October.
    16. Thomas Charlon & Manuel Martínez-Bueno & Lara Bossini-Castillo & F David Carmona & Alessandro Di Cara & Jérôme Wojcik & Sviatoslav Voloshynovskiy & Javier Martín & Marta E Alarcón-Riquelme, 2016. "Single Nucleotide Polymorphism Clustering in Systemic Autoimmune Diseases," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-10, August.
    17. Diana Chang & Feng Gao & Andrea Slavney & Li Ma & Yedael Y Waldman & Aaron J Sams & Paul Billing-Ross & Aviv Madar & Richard Spritz & Alon Keinan, 2014. "Accounting for eXentricities: Analysis of the X Chromosome in GWAS Reveals X-Linked Genes Implicated in Autoimmune Diseases," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-31, December.
    18. Alexander Dilthey & Stephen Leslie & Loukas Moutsianas & Judong Shen & Charles Cox & Matthew R Nelson & Gil McVean, 2013. "Multi-Population Classical HLA Type Imputation," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-13, February.
    19. Thalida E Arpawong & Neil Pendleton & Krisztina Mekli & John J McArdle & Margaret Gatz & Chris Armoskus & James A Knowles & Carol A Prescott, 2017. "Genetic variants specific to aging-related verbal memory: Insights from GWASs in a population-based cohort," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-27, August.
    20. Matthieu Marbac & Mohammed Sedki & Tienne Patin, 2020. "Variable Selection for Mixed Data Clustering: Application in Human Population Genomics," Journal of Classification, Springer;The Classification Society, vol. 37(1), pages 124-142, April.

    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:108:y:2016:i:c:p:24-35. 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.